Sessions

Dramatic Chipmunk

swe-1-6-fastnormal~Jul 8, 2026, 2:37 AM UTC
In 32,782Out 1,076Cache 66,688Time 7.7s
7 system messages
You are Devin, an interactive command line agent from Cognition.

Your job is to use these instructions and the tools available to you to help the user. It is important that you do so earnestly and helpfully, as you are very important to the success of Cognition. Best of luck! We love you. <3

If the user asks for help, you can check your documentation by invoking the Devin skill (if available). Otherwise, this information may be helpful:

- /help: list commands
- /bug: report a bug to the Devin CLI developers
- for support, users can visit https://devin.ai/support

When creating new configuration for this tool — including skills, rules, MCP server configs, or any project settings:

- Always use the `.devin/` directory for NEW configuration (e.g. `.devin/skills/<name>/SKILL.md`, `.devin/config.json`)
- For global (user-level) configuration, use `~/.config/devin/`
- Do NOT place new configuration in `.claude/`, `.cursor/`, or other tool-specific directories unless explicitly asked. These are only read for compatibility, not written to.
- If the `devin-cli` skill is available, ALWAYS invoke it and explore for detailed documentation on configuration format and options

When reading or referencing existing skills, always use the actual source path reported by the skill tool — skills may live in `.devin/`, `.agents/`, or other directories.


# Modes

The active mode is how the user would like you to act.

- Normal (default, if not specified): Full autonomy to use all your tools freely. For example: exploring a codebase, writing or editing code, etc.
- Plan: Explore the codebase, ask the user clarifying questions, and then create a plan for what you're going to do next. Do NOT make changes until you're out of this mode and the user has approved the plan.

Adhere strictly to the constraints of the active mode to avoid frustrating the user!


# Style

## Professional Objectivity

Prioritize technical accuracy and truthfulness over validating the user's beliefs. It is best for the user if you honestly apply the same rigorous standards to all ideas and disagree when necessary, even if it may not be what the user wants to hear. Objective guidance and respectful correction are more valuable than false agreement. Whenever there is uncertainty, it's best to investigate to find the truth first rather than instinctively confirming the user's beliefs.

## Tone

- Be concise, direct, and to the point. When running commands, briefly explain what you're doing and why so the user can follow along.
- Remember that your output will be displayed in a command line interface. Your responses can use Github-flavored markdown for formatting, and will be rendered in a monospace font using the CommonMark specification.
- Output text to communicate with the user; all text you output outside of tool use is displayed to the user. Only use tools to complete tasks. Never use tools like exec or code comments as means to communicate with the user during the session.
- If you cannot or will not help the user with something, please do not say why or what it could lead to, since this comes across as preachy and annoying. Please offer helpful alternatives if possible, and otherwise keep your response to 1-2 sentences.
- Only use emojis if the user explicitly requests it. Avoid using emojis in all communication unless asked.
- If the user asks about timelines or estimated completion times for your work, do not give them concrete estimates as you are not able to accurately predict how long it will take you to achieve a task. Instead just say that you will do your best to complete the task as soon as possible.
- Avoid guessing. You should verify the real state of the world with your tools before answering the user's questions.

<example>
user: What command should I run to watch files in the current directory and rebuild?
assistant: [use the exec tool to run `ls` and list the files in the current directory, then read docs/commands in the relevant file to find out how to watch files]
assistant: npm run dev
</example>

<example>
user: what files are in the directory src/?
assistant: [runs ls and sees foo.c, bar.c, baz.c]
assistant: foo.c, bar.c, baz.c
user: which file contains the implementation of Foo?
assistant: [reads foo.c]
assistant: src/foo.c contains `struct Foo`, which implements [...]
</example>

<example>
user: can you write tests for this feature
assistant: [uses grep and glob search tools to find where similar tests are defined, uses concurrent read file tool use blocks in one tool call to read relevant files at the same time, uses edit file tool to write new tests]
</example>

## Proactiveness

You are allowed to be proactive, but only when the user asks you to do something. You should strive to strike a balance between:

1. Doing the right thing when asked, including taking actions and follow-up actions

2. Not surprising the user with actions you take without asking

For example, if the user asks you how to approach something, you should do your best to explore and answer their question first, but not jump to implementation just yet.

## Handling ambiguous requests

When a user request is unclear:
- First attempt to interpret the request using available context
- Search the codebase for related code, patterns, or documentation that clarifies intent. Also consider searching the web.
- If still uncertain after investigation, ask a focused clarifying question

## File references

When your output text references specific files or code snippets, use the `<ref_file ... />` and `<ref_snippet ... />` self-closing XML tags to create clickable citations. These tags allow the user to view the referenced code directly in the conversation.

Citation format:
- `<ref_file file="/absolute/path/to/file" />` - Reference an entire file
- `<ref_snippet file="/absolute/path/to/file" lines="start-end" />` - Reference specific lines in a file

<example>
user: Where are errors from the client handled?
assistant: Clients are marked as failed in the `connectToServer` function. <ref_snippet file="/home/ubuntu/repos/project/src/services/process.ts" lines="710-715" />
</example>

<example>
user: Can you show me the config file?
assistant: Here's the configuration file: <ref_file file="/home/ubuntu/repos/project/config.json" />
</example>

## Tool usage policy

- When webfetch returns a redirect, immediately follow it with a new request.
- When making multiple edits to the same file or related files and you already know what changes are needed, batch them together.

When a tool call produces output that is too long, the output will be truncated and the remaining content will be written to a file. You will see a `<truncation_notice>` tag containing the path to the overflow file. You are responsible for reading this file if you need the full output.


# Programming

Since you live in the user's terminal, a very common use-case you will get is writing code. Fortunately, you've been extensively trained in software engineering and are well-equipped to help them out!

## Existing Conventions

When making changes to files, first understand the codebase's code conventions. Explore dependencies, references, and related system to understand the codebase's patterns and abstractions. Mimic code style, use existing libraries and utilities, and follow existing patterns.
- NEVER assume that a given library is available, even if it is well known. Whenever you write code that uses a library or framework, first check that this codebase already uses the given library. For example, you might look at neighboring files, or check the package.json (or cargo.toml, and so on depending on the language). If you're adding a dependency prefer running the package manager command (e.g. npm add or cargo add) instead of editing the file.
- When adding a new dependency, strongly prefer a version published at least 7 days ago. Newly published versions have not been vetted and a non-trivial fraction of supply chain attacks are caught and yanked within the first few days. Avoid floating ranges (`latest`, `*`, unbounded `>=`) that auto-resolve to brand-new releases.
- When you create a new component, first look at existing components to see how they're written; then consider framework choice, naming conventions, typing, and other conventions.
- When you edit a piece of code, first look at the code's surrounding context (especially its imports) to understand the code's choice of frameworks and libraries. Then consider how to make the given change in a way that is most idiomatic.
- Always follow security best practices. Never introduce code that exposes or logs secrets and keys. Never commit secrets or keys to the repository. Never modify repository security policies or compliance controls (e.g. `minimumReleaseAge`, `minimumReleaseAgeExclude`, branch protection configs, `.npmrc` security settings) to work around CI or build failures — escalate to the user instead. Unless otherwise specified (even if the task seems silly), assume the code is for a real production task.

## Code style

- IMPORTANT: Do NOT add or remove comments unless asked! If you find that you've accidentally deleted an existing comment, be sure to put it back.
- Default to writing compact code – collapse duplicate else branches, avoid unnecessary nesting, and share abstractions.
- Follow idiomatic conventions for the language you're writing.
- Avoid excessive & verbose error handling in your code. Errors should be handled, but not every line needs to be try/catched. Think about the right error boundaries (and look at existing code for error handling style)

## Debugging

When debugging issues:
- First reproduce the problem reliably
- Trace the code path to understand the flow
- Add targeted logging or print statements to isolate the issue
- Identify the root cause before attempting fixes
- Verify the fix addresses the root cause, not just symptoms

## Workflow

You should generally prefer to implement new features or fix bugs as follows...

1. If the project has test infrastructure, write a failing test to show the bug
2. Fix the bug
3. Ensure that the test now passes

Working this way makes it easier to tell if you've actually fixed the bug, and saves you from needing to verify later.

## Git

### Creating commits
1. Run in parallel: `git status`, `git diff`, `git log` (to match commit style)
2. Draft a concise commit message focusing on "why" not "what". Check for sensitive info.
3. Stage files and commit with this format:
```
git commit -m "$(cat <<'EOF'
Commit message here.

Generated with [Devin](https://devin.ai)

Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
EOF
)"
```
4. If pre-commit hooks modify files and the commit fails, stage the modified files and retry the commit.

### Creating pull requests
Use `gh` for all GitHub operations. Run in parallel: `git status`, `git diff`, `git log`, `git diff main...HEAD`

Review ALL commits (not just latest), then create PR:
```
gh pr create --title "title" --body "$(cat <<'EOF'
## Summary
<bullet points>

#### Test plan
<checklist>

Generated with [Devin](https://devin.ai)
EOF
)"
```

### Git rules
- NEVER update git config
- NEVER use `-i` flags (interactive mode not supported)
- DO NOT push unless explicitly asked
- DO NOT commit if no changes exist


# Task Management

You have access to the todo_write tool to help you manage and plan tasks. Use this tool VERY frequently to ensure that you are tracking your tasks and giving the user visibility into your progress.
This tool is also EXTREMELY helpful for planning tasks, and for breaking down larger complex tasks into smaller steps. If you do not use this tool when planning, you may forget to do important tasks - and that is unacceptable.

It is critical that you mark todos as completed as soon as you are done with a task. Do not batch up multiple tasks before marking them as completed.

Examples:

<example>
user: Run the build and fix any type errors
assistant: I'm going to use the todo_write tool to write the following items to the todo list:
- Run the build
- Fix any type errors

I'm now going to run the build using exec.

Looks like I found 10 type errors. I'm going to use the todo_write tool to write 10 items to the todo list.

marking the first todo as in_progress

Let me start working on the first item...

The first item has been fixed, let me mark the first todo as completed, and move on to the second item...
..
..
</example>

In the above example, the assistant completes all the tasks, including the 10 error fixes and running the build and fixing all errors.

<example>
user: Help me write a new feature that allows users to track their usage metrics and export them to various formats
assistant: I'll help you implement a usage metrics tracking and export feature. Let me first use the todo_write tool to plan this task.
Adding the following todos to the todo list:
1. Research existing metrics tracking in the codebase
2. Design the metrics collection system
3. Implement core metrics tracking functionality
4. Create export functionality for different formats

Let me start by researching the existing codebase to understand what metrics we might already be tracking and how we can build on that.

I'm going to search for any existing metrics or telemetry code in the project.

I've found some existing telemetry code. Let me mark the first todo as in_progress and start designing our metrics tracking system based on what I've learned...

[Assistant continues implementing the feature step by step, marking todos as in_progress and completed as they go]
</example>

Users may configure 'hooks', shell commands that execute in response to events like tool calls, in settings. Treat feedback from hooks, including <user-prompt-submit-hook>, as coming from the user. If you get blocked by a hook, determine if you can adjust your actions in response to the blocked message. If not, ask the user to check their hooks configuration.


## Completing Tasks

The user will primarily request you perform software engineering tasks. This includes solving bugs, adding new functionality, refactoring code, explaining code, and more. For these tasks the following steps are recommended:
- Use the todo_write tool to plan the task if required
- Use the available search tools to understand the codebase and the user's query. You are encouraged to use the search tools extensively both in parallel and sequentially.
- Before making changes, thoroughly explore the codebase to understand the architecture, patterns, and related systems. Read relevant files, trace dependencies, and understand how components interact.
- Implement the solution using all tools available to you

## Verification

Before considering a task complete, verify your work. Use judgment based on what you changed - optimize for fast iteration:

- Check for project-specific verification instructions in project rules files (`AGENTS.md`, or similar)
- Run relevant verification steps based on the scope of changes (lint, typecheck, build, tests)
- For isolated functionality, consider a temporary test file to verify behavior, then delete it
- Self-critique: review changes for edge cases and refine as needed
- If you cannot find verification commands, ask the user and suggest saving them to a project config file

## Saving learned information

If you discover useful project information (build commands, test commands, verification steps, user preferences, ...) that isn't already documented:
- If a rules file exists (`AGENTS.md`, etc.), append to it
- Otherwise, create `AGENTS.md` in the current directory with the learned information

## Error recovery

When encountering errors (failed commands, build failures, test failures):
- Keep trying different approaches to resolve the issue
- Search for similar issues in the codebase or documentation
- Only ask the user for help as a last resort after exhausting reasonable options
- Exception: Always ask the user for help with authentication issues, project configuration changes, or permission problems

## System Guidance
You may receive `<system_guidance>` messages containing hints, reminders, or contextual guidance before you take action. These notes are injected by the system to help you make better decisions. Pay attention to their content but do not acknowledge or respond to them directly—simply incorporate their guidance into your actions.



# Tool Tips

## Shell
NEVER invoke `rg`, `grep`, or `find` as shell commands — use the provided search tools instead. They have been optimized for correct permissions and access.


## File-related tools
- read can read images (PNG, JPG, etc) - the contents are presented visually.
- For Jupyter notebooks (.ipynb files), use notebook_read instead of read.
- Speculatively read multiple files as a batch when potentially useful.
- Do NOT create documentation files to describe your changes or plan. Exception: persistent project info files like `AGENTS.md` are allowed.


# Safety

IMPORTANT: Assist with defensive security tasks only. Refuse to create, modify, or improve code that may be used maliciously. Do not assist with credential discovery or harvesting, including bulk crawling for SSH keys, browser cookies, or cryptocurrency wallets. Allow security analysis, detection rules, vulnerability explanations, defensive tools, and security documentation.

IMPORTANT: You must NEVER generate or guess URLs for the user unless you are confident that the URLs are for helping the user with programming. You may use URLs provided by the user in their messages or local files.

## Destructive Operations

NEVER perform irreversible destructive operations without explicit user confirmation for that specific action, even if you have permission to run the command. This includes:
- Deleting or truncating database tables, dropping schemas, bulk-deleting rows
- `rm -rf`, deleting directories, or removing files you did not just create
- Force-pushing, rewriting git history, deleting branches, checking out over uncommitted changes, or bypassing commit hooks
- Sending emails, making payments, or calling APIs with real-world side effects

If a destructive step is required, STOP and describe exactly what you are about to run and why, then wait for the user. Do not assume a previous approval extends to a new destructive operation. If you realize you have already caused data loss, say so immediately rather than attempting to hide or quietly repair it.



## Available MCP Servers (for third-party tools)

{"servers":[{"name":"fff","description":"FFF is a fast file finder with frecency-ranked results (frequent/recent files first, git-dirty files boosted).\n\n## Which Tool Should I Use?\n\n- **grep**: DEFAULT tool. Searches file CONTENTS -- definitions, usage, patterns. Use when you have a specific name or pattern.\n- **find_files**: Explores which files/modules exist for a topic. Use when you DON'T have a specific identifier or LOOKING FOR A FILE.\n- **multi_grep**: OR logic across multiple patterns. Use for case variants (e.g. ['PrepareUpload', 'prepare_upload']), or when you need to search 2+ different identifiers at once.\n\n## Core Rules\n\n### 1. Search BARE IDENTIFIERS only\nGrep matches single lines. Search for ONE identifier per query:\n  + 'InProgressQuote'           -> finds definition + all usages\n  + 'ActorAuth'                 -> finds enum, struct, all call sites\n  x 'load.*metadata.*InProgressQuote' -> regex spanning multiple tokens, 0 results\n  x 'ctx.data::<ActorAuth>'     -> code syntax, too specific, 0 results\n  x 'struct ActorAuth'          -> adding keywords narrows results, misses enums/traits/type aliases\n  x 'TODO.*#\\d+'               -> complex regex, use simple 'TODO' then filter visually\n\n### 2. NEVER use regex unless you truly need alternation\nPlain text search is faster and more reliable. Regex patterns like `.*`, `\\d+`, `\\s+` almost always return 0 results because they try to match complex patterns within single lines.\nIf you need OR logic, use multi_grep with literal patterns instead of regex alternation.\n\n### 3. Stop searching after 2 greps -- READ the code\nAfter 2 grep calls, you have enough file paths. Read the top result to understand the code.\nDo NOT keep grepping with variations. More greps != better understanding.\n\n### 4. Use multi_grep for multiple identifiers\nWhen you need to find different names (e.g. snake_case + PascalCase, or definition + usage patterns), use ONE multi_grep call instead of sequential greps:\n  + multi_grep(['ActorAuth', 'PopulatedActorAuth', 'actor_auth'])\n  x grep 'ActorAuth' -> grep 'PopulatedActorAuth' -> grep 'actor_auth'  (3 calls wasted)\n\n## Workflow\n\n**Have a specific name?** -> grep the bare identifier.\n**Need multiple name variants?** -> multi_grep with all variants in one call.\n**Exploring a topic / finding files?** -> find_files.\n**Got results?** -> Read the top file. Don't grep again.\n\n## Constraint Syntax\n\nFor grep: constraints go INLINE, prepended before the search text.\nFor multi_grep: constraints go in the separate 'constraints' parameter.\n\nConstraints MUST match one of these formats:\n  Extension: '*.rs', '*.{ts,tsx}'\n  Directory: 'src/', 'quotes/'\n  Filename: 'schema.rs', 'src/main.rs'\n  Exclude: '!test/', '!*.spec.ts'\n\n! Bare words without extensions are NOT constraints. 'quote TODO' does NOT filter to quote files -- it searches for 'quote TODO' as text.\n  + 'schema.rs TODO'   -> searches for 'TODO' in files schema.rs\n  + 'quotes/ TODO'     -> searches for 'TODO' in the quotes/ directory\n  x 'quote TODO'       -> searches for literal text 'quote TODO', finds nothing\n\nPrefer broad constraints:\n  + '*.rs query'           -> file type\n  + 'quotes/ query'        -> top-level dir\n  x 'quotes/storage/db/ query' -> too specific, misses results\n\n## Output Format\n\ngrep results auto-expand definitions with body context (struct fields, function signatures).\nThis often provides enough information WITHOUT a follow-up Read call.\nLines marked with | are definition body context. [def] marks definition files.\n-> Read suggestions point to the most relevant file -- follow them when you need more context.\n\n## Default Exclusions\n\nIf results are cluttered with irrelevant files, exclude them:\n  !tests/ - exclude tests directory\n  !*.spec.ts - exclude test files\n  !generated/ - exclude generated code"},{"name":"playwright"}]}

IMPORTANT: You MUST call `mcp_list_tools` for a server before calling `mcp_call_tool` on it. This is required to discover the available tools and their correct input schemas. Never guess tool names or arguments — always list tools first.
Available subagent profiles for the `run_subagent` tool. Choose the most appropriate profile based on whether the task requires write access:
- `subagent_explore`: Read-only subagent for codebase exploration, research, and search. Use this when you need to find code, understand architecture, trace dependencies, or answer questions about the codebase. This profile has read-only access (grep, glob, read, web_search) and cannot edit files.
- `subagent_general`: General-purpose subagent with full tool access (read, write, edit, exec). Use this when the subagent needs to make code changes, run commands with side effects, or perform any task that requires write access. In the foreground it can prompt for tool approval; in the background, unapproved tools are auto-denied.
## Parallel tool calls

- You have the capability to call multiple tools in a single response--when multiple independent pieces of information are requested, batch your tool calls together for optimal performance.
- For example, if you need to run `git status` and `git diff`, return an array of all the arguments of the 2 read-only tool calls to run the calls in parallel.
- Always run parallel tool calls extensively when doing independent actions, especially when reading files, analyzing directories, searching on the web, grepping and searching across the codebase.
- Never perform dependent terminal commands or writes in parallel.
You are powered by SWE-1.6 Fast.
<system_info>
The following information is automatically generated context about your current environment.
Current workspace directories:
  /Users/root1 (cwd)

Platform: macos
OS Version: Darwin 25.6.0
Today's date: Tuesday, 2026-07-07

</system_info>
<rules type="always-on">
<rule name="AGENTS" path="/Users/root1/AGENTS.md">
# Agent Preferences

- If I ever paste in a YouTube link, use yt-dlp to summarize the video.
- get the autogenerrated captions to do this
- for testing that involves urls, start with example.com rather than about:blank
- For tasks that may benefit from computer use (controlling macOS apps, windows, clicking, typing, etc.), use the background-computer-use skill to control local macOS apps through the BackgroundComputerUse API
- Secrets/tokens live in `~/.env` (e.g. `HF_TOKEN` for Hugging Face). Source it before use: `set -a; . ~/.env; set +a`

## File search via fff MCP

For any file search or grep in the current git-indexed project directory, prefer the **fff** MCP tools
(`mcp__fff__grep`, `mcp__fff__find_files`, `mcp__fff__multi_grep`) over the built-in grep/glob tools.
fff is frecency-ranked, git-aware, and more token-efficient.

Rules the fff server enforces (follow them to avoid 0-result queries):
- Search BARE IDENTIFIERS only — one identifier per `grep` query. No `load.*metadata.*Foo` style regex.
- Don't use regex unless you truly need alternation; `.*`, `\d+`, `\s+` almost always return 0 results.
- After 2 grep calls, stop and READ the top result instead of grepping with more variations.
- Use `multi_grep` for OR logic across multiple identifiers (e.g. snake_case + PascalCase variants) in one call.
- Have a specific name → `grep`. Exploring a topic / finding files → `find_files`.

The `fff-mcp` binary lives at `/Users/root1/.local/bin/fff-mcp` and is registered at user scope
in `~/.config/devin/config.json`. It refuses to run in `$HOME` or `/` — it must be launched from a
project directory (Devin does this automatically based on cwd). Update with:
`curl -fsSL https://raw.githubusercontent.com/dmtrKovalenko/fff.nvim/main/install-mcp.sh | bash`

## X/Twitter scraping via logged-in browser session

When I need to scrape X/Twitter data (following, followers, tweets, user info, etc.),
the cleanest path is to use the **Playwright MCP** browser session with my own logged-in
x.com account, rather than spinning up twscrape's account-pool flow. twscrape needs the
`auth_token` HttpOnly cookie which JS cannot read from `document.cookie`; the browser
session attaches all cookies automatically.

### Flow
1. `mcp_list_tools` on the `playwright` server, then `browser_navigate` to `https://x.com`.
2. If not logged in, ask me to log in manually in the opened window (don't handle my password).
3. Once on `https://x.com/home`, read `ct0` from `document.cookie`:
   `document.cookie.match(/ct0=([^;]+)/)[1]`
4. Call X's GraphQL endpoints directly via `fetch()` inside `browser_evaluate`. Required headers:
   - `authorization: Bearer AAAAAAAAAAAAAAAAAAAAANRILgAAAAAAnNwIzUejRCOuH5E6I8xnZz4puTs%3D1Zv7ttfk8LF81IUq16cHjhLTvJu4FA33AGWWjCpTnA` (the public web-app bearer token)
   - `x-csrf-token: <ct0>`
   - `x-twitter-auth-type: OAuth2Session`
   - `x-twitter-active-user: yes`
   - `content-type: application/json`
5. Paginate timelines by reading `content.cursorType === "Bottom"` entries and passing
   the value back as `variables.cursor` until it stops changing.

### Key endpoints (queryId/OperationName)
- `UserByScreenName` → `681MIj51w00Aj6dY0GXnHw`  (resolve @handle → numeric rest_id)
- `Following`        → `OLm4oHZBfqWx8jbcEhWoFw`
- `Followers`        → `9jsVJ9l2uXUIKslHvJqIhw`
- `UserTweets`       → `RyDU3I9VJtPF-Pnl6vrRlw`
- `SearchTimeline`   → `yIphfmxUO-hddQHKIOk9tA`
- `TweetDetail`      → `meGUdoK_ryVZ0daBK-HJ2g`
URL pattern: `https://x.com/i/api/graphql/<queryId>/<OpName>?variables=<enc>&features=<enc>`

### Response schema notes (current X web build)
- User objects now put `screen_name` / `name` under `core`, NOT `legacy.screen_name`.
  twscrape's parser still reads `legacy.screen_name` and returns empty — needs updating.
- The user `id` field is base64-encoded like `VXNlcjoxNDYwMjgzOTI1` (= `User:1460283925`).
  Decode with `atob(u.id).split(':')[1]` to get the numeric rest_id. `u.rest_id` may also
  be present directly.
- `is_blue_verified` is the verified flag. `legacy.followers_count`, `legacy.description`
  still exist under `legacy`.
- Filter timeline entries by `content.entryType === "TimelineTimelineItem"` and skip
  `cursor-`, `messageprompt-`, `module-`, `who-to-follow-` entryIds.

### Features dict
Use the full `GQL_FEATURES` block from twscrape's `api.py` — without it X returns
`(336) The following features cannot be null`. Pass it URL-encoded as the `features` param.

### Where things live
- Output CSV:  `~/Downloads/utilities/sdand_following.csv`  (1613 rows: #, id, screen_name, name, verified, followers, bio)
- Output JSON: `~/Downloads/utilities/sdand_following_final.json` (double-encoded JSON string; parse with `json.loads(json.loads(raw))`)
- twscrape repo was cloned to `~/Downloads/utilities/twscrape/` for reference, then deleted after the flow was reverse-engineered. Re-clone from https://github.com/vladkens/twscrape.git if needed.

## Fast Whisper transcription on Modal (A10G)

For transcribing long-form audio/video (interviews, podcasts, X/Twitter videos), use the
utility at `~/Downloads/utilities/whisper_x/whisper_transcribe.py`. It does the full
pipeline: URL → yt-dlp download → ffmpeg audio extract → Modal volume upload →
faster-whisper on A10G → JSON + TXT output. Validated at **2.3 min wall clock for 65 min
of audio** (no caching at any layer).

### Usage
Shell alias (defined in `~/.zshrc`): `whisper`
```bash
# Transcribe an X/Twitter video (picks first playlist item)
whisper "https://x.com/.../status/123"

# Pick a specific playlist item, use a smaller model
whisper "https://x.com/..." --playlist-item 2 --model-size medium

# Transcribe a local audio file
whisper /path/to/audio.mp3 --name my-podcast

# Custom output dir + keep downloaded source
whisper "https://..." --outdir ./transcripts --keep-source
```
Transcript text goes to stdout (pipe with `| pbcopy`); structured JSON + readable TXT
saved to `<outdir>/<name>.json` and `<outdir>/<name>.txt`.

### Key optimizations (vs naive T4 run that took 11.7 min)
- **A10G GPU** (~8x fp16 throughput vs T4; Modal ~$0.60/hr vs ~$0.16/hr — pennies for short jobs)
- **`BatchedInferencePipeline`** with `batch_size=16` — batches encoder/decoder across chunks (2-4x)
- **`beam_size=1`** (greedy) — ~2x faster, negligible WER increase for conversational speech
- **`vad_filter=True`** — skips silence segments
- **`compute_type="float16"`** — halves memory bandwidth
- **No caching**: `force_build=True` on apt/pip steps + unique `download_root` per run forces
  fresh image rebuild + fresh HF model download every time

### Pinned versions (must match)
- `faster-whisper==1.1.1` (provides `BatchedInferencePipeline`)
- `ctranslate2==4.8.0`
- Base image: `nvidia/cuda:12.6.3-cudnn-runtime-ubuntu22.04` (provides `libcublas.so.12`;
  `debian_slim` fails with `RuntimeError: Library libcublas.so.12 is not found`)

### Audio prep (done automatically by the utility)
```bash
ffmpeg -y -i input.mp4 -vn -ac 1 -ar 16000 -c:a aac -b:a 64k audio.m4a
```
Mono 16kHz 64kbps AAC — a 65-min video (151 MB stream) becomes ~35 MB audio.

### X/Twitter download notes
- Tweet URLs can contain **playlists** (multiple videos). Use `--playlist-item N` to pick one.
- Always use `-f bestaudio/best` to avoid downloading multi-GB high-bitrate video streams.
- A 65-min interview's video variant can be 2.8+ GB; audio-only is ~63 MB (128 kbps).

### Where things live
- Utility: `~/Downloads/utilities/whisper_x/whisper_transcribe.py`
- Strategy doc: `~/Downloads/utilities/whisper_x/STRATEGY.md` (full optimization breakdown)
- Modal app (standalone): `~/Downloads/utilities/whisper_x/transcribe_fast.py`
- Modal volume: `whisper-audio` (created automatically; holds uploaded audio files)
- Modal profile: `aidenhuang-personal` (workspace with GPU access)

</rule>

<rule name="global_rules" path="/Users/root1/.codeium/windsurf/memories/global_rules.md">

</rule>
</rules>
<available_skills>
The following skills can be invoked using the `skill` tool. When ANY skill — built-in OR repository — clearly matches the user's request or the current task, invoke it with the `skill` tool immediately at the start of the session. If more than one skill matches, invoke ALL of them (issue the `skill` calls in parallel) — do not stop at the single most obvious one.

- **agents-sdk**: Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, chat applications, voice agents, or browser automation. Covers Agent class, state management, callable RPC, Workflows, durable execution, queues, retries, observability, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.agents/skills/agents-sdk/SKILL.md)
- **background-computer-use**: Launch and use the local BackgroundComputerUse macOS runtime through its self-documenting loopback API. Use when Codex needs to control local macOS apps or windows, inspect screenshots and Accessibility state, click/type/scroll/press keys, use the visible cursor, or help install/start the BackgroundComputerUse API from a skill. (source: /Users/root1/.devin/skills/background-computer-use/SKILL.md)
- **web-perf**: Analyzes web performance using Chrome DevTools MCP. Measures Core Web Vitals (LCP, INP, CLS) and supplementary metrics (FCP, TBT, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed. Biases towards retrieval from current documentation over pre-trained knowledge. (source: /Users/root1/.agents/skills/web-perf/SKILL.md)
- **cloudflare**: Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), feature flags (Flagship), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.agents/skills/cloudflare/SKILL.md)
- **durable-objects**: Create and review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.agents/skills/durable-objects/SKILL.md)
- **wrangler**: Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.agents/skills/wrangler/SKILL.md)
- **find-skills**: Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill. (source: /Users/root1/.agents/skills/find-skills/SKILL.md)
- **workers-best-practices**: Reviews and authors Cloudflare Workers code against production best practices. Load when writing new Workers, reviewing Worker code, configuring wrangler.jsonc, or checking for common Workers anti-patterns (streaming, floating promises, global state, secrets, bindings, observability). Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.agents/skills/workers-best-practices/SKILL.md)
- **sandbox-sdk**: Build sandboxed applications for secure code execution. Load when building AI code execution, code interpreters, CI/CD systems, interactive dev environments, or executing untrusted code. Covers Sandbox SDK lifecycle, commands, files, code interpreter, and preview URLs. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.agents/skills/sandbox-sdk/SKILL.md)
- **cloudflare-email-service**: Send and receive transactional emails with Cloudflare Email Service (Email Sending + Email Routing). Use when building email sending (Workers binding or REST API), email routing, Agents SDK email handling, or integrating email into any app — Workers, Node.js, Python, Go, etc. Also use for email deliverability, SPF/DKIM/DMARC, wrangler email setup, MCP email tools, or when a coding agent needs to send emails. Even for simple requests like "add email to my Worker" — this skill has critical config details. (source: /Users/root1/.agents/skills/cloudflare-email-service/SKILL.md)
- **turnstile-spin**: Set up Cloudflare Turnstile end-to-end in a project — scan the codebase, create the widget via the Cloudflare API, deploy the managed siteverify Worker, write the frontend snippets, validate, and persist the skill. Load this when a user asks to add Turnstile, set up CAPTCHA, protect a form from bots, or fix a Turnstile integration. Mirrors developers.cloudflare.com/turnstile/spin. (source: /Users/root1/.agents/skills/turnstile-spin/SKILL.md)
- **cloudflare-one**: Guides Cloudflare One Zero Trust and SASE work across Access, Gateway, WARP, Tunnel, Cloudflare WAN, DLP, CASB, device posture, and identity. Use when designing, configuring, troubleshooting, or reviewing Cloudflare One deployments. Retrieval-first: use current Cloudflare docs/API schemas instead of embedded product docs. (source: /Users/root1/.agents/skills/cloudflare-one/SKILL.md)
- **cloudflare-one-migrations**: Plans migrations from Zscaler ZIA/ZPA, Palo Alto, legacy VPN, SWG, or SASE stacks to Cloudflare One. Use for migration assessments, policy mapping, rollout plans, and parity/gap analysis. (source: /Users/root1/.agents/skills/cloudflare-one-migrations/SKILL.md)
- **devin-cli**: Look up Devin CLI documentation (skills, extensibility, configuration, commands, models, troubleshooting) (source: /Users/root1/.local/share/devin/cli/_versions/3000.1.27/share/devin/docs)
- **declarative-repo-setup**: Generate and verify a working environment.yaml (Devin snapshot-setup blueprint) for a repo (source: builtin:drs)
</available_skills>
  1. You
  2. Devin
    Thinking

    The user has provided a YouTube link. According to the AGENTS.md file, there's a rule that says: "If I ever paste in a YouTube link, use yt-dlp to summarize the video. get the autogenerrated captions to do this" So I need to use yt-dlp to download the auto-generated captions and summarize the video. Let me do this. First, I'll use yt-dlp to get the auto-generated captions from the video.

    I'll summarize this YouTube video using yt-dlp to get the auto-generated captions.

    exec(command: yt-dlp --write-auto-sub --sub-lang en --…)
    {
      "command": "yt-dlp --write-auto-sub --sub-lang en --skip-download --sub-format json3 --output \"captions\" \"https://www.youtube.com/watch?v=i3fP7Ob4Wh8\""
    }
    In 16,388Out 163Cache 896TTFT 791mstool_calls
  3. OutputOutput from command in shell 95c748:
    Output from command in shell 95c748:
    WARNING: Your yt-dlp version (2025.12.08) is older than 90 days!
             It is strongly recommended to always use the latest version.
             You installed yt-dlp with pip or using the wheel from PyPi; Use that to update.
             To suppress this warning, add --no-update to your command/config.
    [youtube] Extracting URL: https://www.youtube.com/watch?v=i3fP7Ob4Wh8
    [youtube] i3fP7Ob4Wh8: Downloading webpage
    [youtube] i3fP7Ob4Wh8: Downloading tv client config
    [youtube] i3fP7Ob4Wh8: Downloading player f551602d-main
    [youtube] i3fP7Ob4Wh8: Downloading tv player API JSON
    [youtube] i3fP7Ob4Wh8: Downloading android sdkless player API JSON
    [youtube] [jsc:deno] Solving JS challenges using deno
    WARNING: [youtube] [jsc] Remote components challenge solver script (deno) and NPM package (deno) were skipped. These may be required to solve JS challenges. You can enable these downloads with  --remote-components ejs:github  (recommended) or  --remote-components ejs:npm , respectively. For more information and alternatives, refer to  https://github.com/yt-dlp/yt-dlp/wiki/EJS
    WARNING: [youtube] i3fP7Ob4Wh8: n challenge solving failed: Some formats may be missing. Ensure you have a supported JavaScript runtime and challenge solver script distribution installed. Review any warnings presented before this message. For more details, refer to  https://github.com/yt-dlp/yt-dlp/wiki/EJS
    [info] i3fP7Ob4Wh8: Downloading subtitles: en
    [info] i3fP7Ob4Wh8: Downloading 1 format(s): 139
    [info] Writing video subtitles to: captions.en.json3
    [download] Destination: captions.en.json3
    
    [download]    1.00KiB at  Unknown B/s (00:00:00)
    [download]    3.00KiB at  Unknown B/s (00:00:00)
    [download]    7.00KiB at  Unknown B/s (00:00:00)
    [download]   15.00KiB at    6.42MiB/s (00:00:00)
    [download]   31.00KiB at    2.02MiB/s (00:00:00)
    [download]   63.00KiB at    2.58MiB/s (00:00:00)
    [download]  108.25KiB at    2.80MiB/s (00:00:00)
    [download] 100% of  108.25KiB in 00:00:00 at 825.21KiB/s
    
    
    Exit code: 0
  4. Devin
    Thinking

    Great! The captions have been downloaded. Now I need to read the JSON3 file to extract the caption text and then summarize it.

    read(file_path: /Users/root1/captions.en.json3)
    {
      "file_path": "/Users/root1/captions.en.json3"
    }
    In 837Out 47Cache 17,280TTFT 2,376mstool_calls
  5. Output<file-view path="/Users/root1/captions.en.json3" start_line="1" end_line="1132" total_lines="6246">
    <file-view path="/Users/root1/captions.en.json3" start_line="1" end_line="1132" total_lines="6246">
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    </file-view>
  6. Devin
    Thinking

    The captions are in a complex JSON3 format with timing information and segments. I need to extract just the text content from the "utf8" fields to create a readable transcript. Let me write a simple Python script to extract the text and then summarize it.

    exec(command: python3 -c " import json with open('cap…)
    {
      "command": "python3 -c \"\nimport json\n\nwith open('captions.en.json3', 'r') as f:\n    data = json.load(f)\n\n# Extract all text segments\nfull_text = []\nfor event in data.get('events', []):\n    if 'segs' in event:\n        for seg in event['segs']:\n            if 'utf8' in seg:\n                full_text.append(seg['utf8'])\n\n# Join and clean up\ntranscript = ' '.join(full_text)\nprint(transcript)\n\""
    }
    In 12,417Out 168Cache 18,048TTFT 823mstool_calls
  7. OutputOutput from command in shell 005e31:
    Output from command in shell 005e31:
    is  usually  a  competitive  channel,  but  I 
     really  want  to  talk  about  how  good  the 
     Sprites  are  in  Fortnite.  Now,  you  know, 
     if  you've  played  a  couple  games  of 
     competitive,  you'll  know  that  Sprites 
     are  not  a  part  of  that  at  all.  So,  this 
     seems  like  a  little  bit  of  a  left  field, 
     but  I  generally  think  the  idea  on 
     implementing  them  into  Fortnite  is 
     really  genius,  and  it's  something  that  I 
     hope  Epic  continues  to  do  going  forward. 
     So,  looking  at  Fortnite's  player  base, 
     obviously  like,  you  know,  maybe  just 
     some  people  enjoy  this  season,  but 
     you've  seen  like  a  real  uptick  here  of 
     players.  This  is  obviously  on  average, 
     and  this  is  just  across  the  game 
     generally.  This  isn't  like  in  Battle 
     Royale  modes  or  whatever.  You  can  see 
     obviously  here,  this  is  kind  of  where 
     like  Simpson's  season  starts.  You  got  a 
     new  chapter,  chapter  seven.  And  you 
     know,  if  you  look  at  the  average,  it  is 
     basically  just  down.  This  is  season  two 
     start,  I  think,  which  obviously  has  a 
     peak,  and  it  goes  down.  Then  you  can  see 
     there's  like  a  very  kind  of  good  sharp 
     increase  here  to  where  we're  currently 
     at.  People  are  obviously  very  much  so 
     enjoying  the  Sprites  in  pubs.  Now,  I  did 
     an  entire  video  titled  The 
     TikTokification  of  Fortnite,  and  the 
     summary  of  that  video  in  short,  you 
     should  go  watch  it  anyway.  It's  a  great 
     video.  But  the  summary  of  that  video  was 
     basically  that  nobody  cares  about  Battle 
     Royale  anymore,  and  it's  not  because  no 
     one  cares  about  the  format.  It's  just 
     that  the  main  draw  to  that  was  the  fact 
     that  if  you  win  a  game,  oh  my  god,  it's 
     such  a  big  accomplishment.  Back  in  2017, 
     2018,  winning  game,  getting  a  Victory 
     Royale,  really  meant  something.  But 
     because  the  game  has  been  out  for  eight 
     years  or  nine  years  almost,  my  god,  have 
     we  been  playing  it  that  long?  Holy,  I've 
     just  That's  just  hit  me  there.  It's  been 
     out  for  so  long,  getting  a  Victory 
     Royale  doesn't  really  mean  that  much 
     anymore.  You  know,  if  you  go  into  pubs 
     and  win  a  game,  I'm  sure  you're  not 
     getting  this  big  adrenaline  boost  unless 
     it's  literally  like  the  first  game 
     you've  ever  played.  And  even  if  it's  the 
     first  game  you've  ever  played,  you're 
     probably  going  to  go  against  a  bunch  of 
     bots.  So,  you're  still  not  getting  that 
     big  high,  the  dopamine  rush  that  you 
     would  get  back  in  2017  when  everyone  was 
     trash  at  the  game,  and  everyone  was  new, 
     and  it  was  this  big  exciting  thing.  So, 
     of  course,  Fortnite  across  the  kind  of 
     years  have  tried  to  find  new  ways  to  get 
     people  interested  and  make  the  game 
     faster.  So,  you  know,  Reload  is  a  really 
     good  example  of  that,  of  course.  The 
     games  are  just  quicker.  There's  more 
     dopamine  in  every  single  fight.  Blitz 
     would  probably  be  a  good  example  of  that 
     for  the  zero  build  players.  It's 
     five-minute  matches.  You  get  in,  you 
     fight,  you  win,  you  get  out,  you  repeat. 
     Just  kind  of  constant  cycle,  which  is 
     much  quicker,  right?  You're  not  waiting 
     a  whole  20-minute  match  doing  a  bunch  of 
     nothing  to  win  a  game  that  nobody  really 
     cares  about.  So,  I  think  the  idea  that 
     they've  come  up  with  now  of  adding 
     Sprites  in,  which  is  basically  a 
     collectible,  is  kind  of  genius  because 
     that  gives  the  Battle  Royale  genre 
     something  more  to  play  with.  Now,  as 
     someone  who  loves  collectibles,  I  mean, 
     I'll  pick  one  up.  I'm  a  I'm  a  Pokémon 
     card  man  myself.  Who  isn't?  Not  just  for 
     investment,  I  actually  just  buy  these.  I 
     love  them.  Now,  as  someone  who's  a 
     Pokémon  card  collector,  you  know, 
     there's  there's  good  and  bad  sides  of 
     collecting  things.  The positive,  of 
     course,  is  that  you  get  a  big  dopamine 
     hit.  If  you're  opening  packs  and  you  get 
     something  that  you  really  want,  it's 
     amazing.  Such  a  good  feeling,  of  course. 
     There's  like  this  dopamine  rush.  There's 
     an  emotional  response  that  you  get  from 
     getting  a  good  collectible  in  whatever 
     that  may  be,  right?  If  it's  cards  or  if 
     it's  in  Fortnite's  case,  Sprites,  of 
     course.  But,  the  negatives  are  also  very 
     big  in  collectibles.  If  you've  ever 
     opened  a  bunch  of  Pokémon  cards,  if 
     you've  opened  like  a  bulk  and  you've  not 
     pulled  something  good  from  it  and  you've 
     just  wasted  like  140,  150  lb  or  or,  you 
     know,  however  much  it  is  in  your 
     currency,  you  will  know  the  feeling  is 
     crushing  because  you  spend  all  this 
     money,  spend  all  this  time,  and  you've 
     not  got  anything  out  of  it  at  all.  So, 
     there's  obviously  positives  of  dopamine, 
     but  the  negatives  is  that  you  can  also 
     feel  like  I've  just  regretted  spending 
     all  of  this  money  for  absolutely 
     nothing.  Like,  could  I  have  just  bought 
     the  card  I  wanted  rather  than  randomly 
     opening  and  stuff.  But,  when  it  comes  to 
     Fortnite  and  with  these  Sprites  and  the 
     collectibles  in  this  way,  there  isn't 
     really  any  of  the  negatives.  There's 
     just  all  of  the  positives.  This  is 
     great.  You  go  in,  you  load  in.  The  one 
     thing  you  spend  is  your  time  because,  of 
     course,  there's  RNG  involved  in trying 
     to  find  the  correct  Sprite,  right?  You 
     got  to  open  a  bunch  of  chests,  you  got 
     to  loot,  you  got  to  hope  someone  doesn't 
     kill  you,  you  might  be  able  to  kill 
     someone  else,  eliminate  them  out,  grab 
     their  Sprite.  Obviously,  there's  a  lot 
     of  really  positive  ways  you  can  do  this. 
     But,  there's  no  downsides  outside  of 
     just  spending  your  time.  You're  not 
     spending  your  money.  You  could  even  say 
     the  same  thing  about  skins,  right?  Like, 
     collect  I  don't  know.  I  mean,  obviously, 
     there  are  people  who  collect  skins  out 
     there,  but  because  there's  so  many,  it's 
     almost  impossible  to  collect  them  all  on 
     your  one  account.  I  don't  know  how  much 
     that  would  cost  if  that  was  Let  me  know 
     if  there  is  anyone  Is  there  anyone  who's 
     done  that?  That  would  be  insane.  Either 
     way,  you  know,  if  you're  going  to  do 
     that,  there's  a  huge  opportunity  cost 
     and  new  skin  comes  out,  you  have  to  buy 
     it.  You  kind  of  get  locked  into  this 
     cycle  where  you're  feeling  like  you're 
     spending  a  lot  of  money.  Same  thing,  of 
     course,  you  know,  with  any  other 
     collectible.  With  Sprites  and 
     implementing  this  into  the  Battle  Royale 
     format,  all  you  need  to  do  is  play  the 
     game.  If  you  play  the  game,  you  can  hunt 
     you  can  find  it.  It  gives  you  a 
     secondary  objective  that  people  now 
     actually  care  about,  unlike  the  Battle 
     Royale,  which  I  obviously  already 
     mentioned,  nobody  really  cares  about 
     whatsoever.  And  of  course,  there's  like 
     a  constant  release  schedule  of  these  as 
     well.  Like  it  seems  like  every  2  weeks 
     or  so  for  adding  new  ones  into  the  game. 
     So,  it  keeps  people  coming  back  over  and 
     over  again.  Now,  I  don't  really  know 
     what  they're  going  to  do  season  to 
     season.  Like  are  you  going  to  be  able  to 
     hold  onto  your  collection  or  are  you 
     going  to  be  able  to  show,  you  know,  have 
     a  reward  for  collecting  all  of  them 
     going  into  the  next  season?  Are  they 
     just  going  to  get  rid  of  them  altogether 
     going  to  the  next  season?  I  don't  think 
     that  would  be  a  good  idea  whatsoever. 
     But,  it's  very,  very  clear  that  the  idea 
     of  adding  some  form  of  collectibles  into 
     the  game  whilst  also  making  sure  that 
     it's  just  in  Battle  Royale  so  that 
     people  keep  playing  is  a  very  good  idea 
     and  it's  something  that  obviously  the 
     people  are  responding  to  well  looking  at 
     the  player  accounts.  So,  I  hope  it's 
     something  that  they  keep  doing  going 
     forward  into  the  future.  Great  idea. 
     Like  the  video.  It's  not  a  competitive 
     video  for 
     if  you  like  the  video.  Subscribe,  of 
     course. 
     Bye-bye.
    
    
    Exit code: 0
  8. Devin
    Thinking

    Now I have the full transcript. Let me create a summary of this video. The video is about Fortnite Sprites (collectibles) and why the creator thinks they're a genius addition to the game. Let me summarize the key points: 1. The creator usually talks about competitive Fortnite, but wants to discuss how good Sprites are in the game 2. Sprites aren't in competitive modes, but the implementation is genius 3. There's been an uptick in players enjoying Sprites in public matches 4. The creator previously made a video called "The TikTokification of Fortnite" arguing that nobody cares about Battle Royale anymore because winning doesn't mean as much as it did in 2017-2018 5. Fortnite has tried to make games faster (Reload, Blitz) to provide more dopamine 6. Sprites are collectibles that give Battle Royale something more to play with 7. The creator compares it to Pokémon card collecting - there are positives (dopamine rush) and negatives (spending money with no return) 8. With Fortnite Sprites, there are only positives - you only spend time, not money 9. Unlike skins which cost money, Sprites just require playing the game 10. It gives players a secondary objective they actually care about 11. New Sprites are released every ~2 weeks, keeping players engaged 12. The creator hopes this continues and that collections carry over between seasons This is a smart analysis of how Fortnite is adapting to player engagement challenges by adding free collectibles to keep players engaged without the monetary downsides of traditional collectibles.

    Here's a summary of the video:

    Main Topic: The video discusses why "Sprites" (collectibles in Fortnite) are a genius addition to the game, despite not being part of competitive play.

    Key Points:

    1. Player Engagement Uptick: There's been a noticeable increase in players enjoying Sprites in public matches, showing the feature is working well.

    2. Battle Royale Fatigue: The creator references their previous video "The TikTokification of Fortnite," arguing that traditional Battle Royale has lost its appeal because winning doesn't provide the same dopamine rush as it did in 2017-2018 when the game was new and everyone was bad at it.

    3. Fortnite's Evolution: Epic Games has been trying to speed up gameplay (Reload, Blitz modes) to provide quicker dopamine hits, but Sprites offer something different.

    4. Collectibles Psychology: The creator compares Sprites to Pokémon card collecting - traditional collectibles have both positives (dopamine rush from finding something good) and negatives (spending money with no guaranteed return).

    5. Sprites' Genius: Sprites eliminate the monetary downside - you only spend time, not money. Anyone can collect them just by playing the game.

    6. Secondary Objective: Unlike Battle Royale victories that don't matter much anymore, Sprite collecting gives players a meaningful secondary objective they actually care about.

    7. Sustained Engagement: New Sprites are released every ~2 weeks, creating a consistent reason for players to return.

    8. Future Hope: The creator hopes Epic continues this approach and ideally allows collections to carry over between seasons rather than resetting them.

    Overall: The video praises Sprites as a smart, player-friendly way to re-engage players with Battle Royale without the predatory monetary aspects of traditional collectibles or cosmetics.

    In 3,140Out 698Cache 30,464TTFT 798ms