Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/itechmeat/llm-code/github-stars-organizernpx skills add itechmeat/llm-code --skill github-stars-organizergit clone --depth 1 https://github.com/itechmeat/llm-codeWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00078 | $0.02689 |
| Opus 5 | $0.00039 | $0.01345 |
| Sonnet 5 | $0.00016 | $0.00538 |
| Haiku 4.5 | $0.00008 | $0.00269 |
Grade A, and why
github-stars-organizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Stars Organizer
Organize a user's GitHub starred repositories by reusing existing lists, creating only a small number of broad missing lists, and adding unlisted repositories to the right places.
This skill is for organizing starred repositories, not for general GitHub account maintenance.
Default stance: be conservative, review-first, and additive. A bad list assignment is worse than leaving a repository unfiled for later review.
Required Tooling
- Preferred browser automation skill: chrome-cdp
- A compatible equivalent is acceptable only if it can:
- control an authenticated local browser session
- read the GitHub Stars page
- inspect repository list membership
- create lists
- add repositories to lists
If chrome-cdp or an equivalent browser automation skill is unavailable, stop and say that authenticated browser automation is required.
Remote Debugging Prerequisite
If Chrome remote debugging is not enabled yet, tell the user to do this first:
- Open
chrome://inspect/#remote-debugging - Enable remote debugging / remote target discovery
- Make sure GitHub is logged in in that Chrome profile
- Confirm the local debugging endpoint is available, commonly
127.0.0.1:9222 - Approve any Chrome "Allow debugging" prompt for the GitHub tab if it appears
Do not proceed until browser automation can reach the GitHub tab.
Inputs
The user should provide at least one of:
- GitHub username
- GitHub profile URL
- GitHub Stars URL
Do not hardcode any specific account, repository, or list names.
Default Safety Rules
- Default to additive organization only
- Do not unstar repositories
- Do not remove repositories from lists
- Do not rename or delete lists
- If a repository is already in one or more lists, skip it by default
- Reuse existing lists before creating new ones
- Keep the final list system compact and reusable
- Prefer one primary list per repository
- Add a second list only when it clearly improves retrieval
- Add a third list only for genuine cross-domain repositories
- If confidence is not high, do not guess
- Report ambiguous repositories instead of forcing them into a weak category
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 306 lines · 78 tokens per session scan A ea0472292508
github-stars-organizer is a skill published in the GitHub repository itechmeat/llm-code (22 stars, last pushed 1mo ago), licensed MIT. It adds 78 tokens to every session and 2,689 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…