Minimizing Ty Ecosystem Changes
astral-sh/ruff
A skill your agent uses when a user says "minimize this ty ecosystem change", "reproduce this ecosystem result", "investigate a primer difference", "investigate a mypyprimer difference"…
Run the CI gate on your machine so it agrees with the runner — deriving the exact command, paths, markers, and env from the workflow file instead of the Makefile, unblocking gate steps that…
$ npx skills add kajisho5/ffmpeg-skill --skill reproducing-ci-locally -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install kajisho5/ffmpeg-skill reproducing-ci-locally --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/kajisho5/ffmpeg-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/reproducing-ci-locally .claude/skills/reproducing-ci-locally && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "reproducing-ci-locally" agent skill from https://github.com/kajisho5/ffmpeg-skill/tree/main/.claude/skills/reproducing-ci-locally into .claude/skills/reproducing-ci-locally/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reproducing-ci-locally", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/kajisho5/ffmpeg-skill/tree/main/.claude/skills/reproducing-ci-locallyType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add kajisho5/ffmpeg-skill --skill reproducing-ci-locally -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install kajisho5/ffmpeg-skill reproducing-ci-locally --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kajisho5/ffmpeg-skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/reproducing-ci-locally .agents/skills/reproducing-ci-locally && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "reproducing-ci-locally" agent skill from https://github.com/kajisho5/ffmpeg-skill/tree/main/.claude/skills/reproducing-ci-locally into .agents/skills/reproducing-ci-locally/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reproducing-ci-locally", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add kajisho5/ffmpeg-skill --skill reproducing-ci-locally -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install kajisho5/ffmpeg-skill reproducing-ci-locally --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kajisho5/ffmpeg-skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/reproducing-ci-locally .cursor/skills/reproducing-ci-locally && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "reproducing-ci-locally" agent skill from https://github.com/kajisho5/ffmpeg-skill/tree/main/.claude/skills/reproducing-ci-locally into .cursor/skills/reproducing-ci-locally/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reproducing-ci-locally", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/kajisho5/ffmpeg-skill.git --path .claude/skills/reproducing-ci-locally--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add kajisho5/ffmpeg-skill --skill reproducing-ci-locally -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install kajisho5/ffmpeg-skill reproducing-ci-locally --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kajisho5/ffmpeg-skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/reproducing-ci-locally .gemini/skills/reproducing-ci-locally && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "reproducing-ci-locally" agent skill from https://github.com/kajisho5/ffmpeg-skill/tree/main/.claude/skills/reproducing-ci-locally into .gemini/skills/reproducing-ci-locally/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reproducing-ci-locally", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install kajisho5/ffmpeg-skill reproducing-ci-locallyInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add kajisho5/ffmpeg-skill --skill reproducing-ci-locally -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/kajisho5/ffmpeg-skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/reproducing-ci-locally .github/skills/reproducing-ci-locally && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "reproducing-ci-locally" agent skill from https://github.com/kajisho5/ffmpeg-skill/tree/main/.claude/skills/reproducing-ci-locally into .github/skills/reproducing-ci-locally/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reproducing-ci-locally", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add kajisho5/ffmpeg-skill --skill reproducing-ci-locally -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install kajisho5/ffmpeg-skill reproducing-ci-locally --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kajisho5/ffmpeg-skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/reproducing-ci-locally .opencode/skills/reproducing-ci-locally && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "reproducing-ci-locally" agent skill from https://github.com/kajisho5/ffmpeg-skill/tree/main/.claude/skills/reproducing-ci-locally into .opencode/skills/reproducing-ci-locally/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reproducing-ci-locally", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
reproducing-ci-locallyRun the CI gate on your machine so it agrees with the runner — deriving the exact command, paths, markers, and env from the workflow file instead of the Makefile, unblocking gate steps that…
Reproducing CI Locally is an agent skill from kajisho5/ffmpeg-skill. Run the CI gate on your machine so it agrees with the runner — deriving the exact command, paths, markers, and env from the workflow file instead of the Makefile, unblocking gate steps that short-circuit and hide the next failure, pinning the linter version CI resolves, building the interpreter/toolchain environment the runner builds, and confirming the run is green instead of explaining a red job away. Use when a check passes locally but fails in CI (or the reverse), when a lint/format job goes red on an…
Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Linting and formatting. It works with Ruff. The licence is MIT.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 1f7e7e3. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
ruffuvmakepytestpythonghnpmuvxnpxcargobrewchocoFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
github.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Reproducing CI Locally loads about 2.8k tokens when it runs. Until then it costs about 164 tokens; SKILL.md has 1,287 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
Keep those values in a gitignored `.env.ci` copied from the workflow's `env:`set -a; . ./.env.ci; set +aAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from kajisho5/ffmpeg-skill at commit 1f7e7e3, republished under its MIT licence (© kajisho5). 1,287 words, ~2,847 tokens.
.claude/skills/reproducing-ci-locally/SKILL.md (or your agent's skills folder).A local check is only useful if it runs the same thing the runner runs. Most "green locally, red in CI" failures are not bugs in the code — they are a difference between two commands: different paths, different test markers, different env, a different linter version, or a different interpreter.
The fix is mechanical: derive the local command from the workflow file, not from the Makefile, not from habit, not from what the last repo used.
The workflow is the contract. The Makefile is a convenience that drifts from it.
# What the gate actually is, in order
sed -n '/jobs:/,$p' .github/workflows/ci.yml
# Every command CI runs, across all workflows
grep -rn "run:" .github/workflows/Copy out four things, verbatim:
ruff check app tests scripts is not
ruff check .).-k filters, which suites are excluded.env: block, and the runtime/toolchain versions in setup-* steps.Each of those four is a distinct way to get a wrong answer locally.
Paths. If CI lints app tests scripts and you run ruff check ., you get
findings from directories CI never looks at — a red that isn't a merge blocker
and shouldn't be "fixed" in an unrelated PR. Run it the narrow way to reproduce
the gate; run it the wide way only when you're deliberately auditing.
Markers. A suite-wide make test that excludes one marker is not the CI
gate if CI excludes six. Live-credential integration tests deselected in CI will
run locally, hit a fake key, and fail in a way that looks like a regression:
# Wrong: local shorthand — pulls in suites CI never runs
pytest -m "not browser"
# Right: the full expression, copied from the workflow
pytest -m "not browser and not slow and not load and not integration"Env. Config objects instantiated at import time (a settings singleton at
module scope, an engine built when the module loads) make collection fail
without the workflow's variables — a wall of "Field required" errors that looks
like a broken suite. Mirror the env: block, including the shape of values:
if CI passes a Postgres URL and the module builds a pooled engine, a local
SQLite URL raises on arguments that dialect rejects before a single test runs.
Keep those values in a gitignored .env.ci copied from the workflow's env:
block, so the local command is the workflow command plus one set -a:
set -a; . ./.env.ci; set +a
pytest -m "not browser and not slow and not load and not integration"Gate steps run in order and the job stops at the first red. So the CI log shows you one failure even when three are waiting:
- run: ruff check . # fails here …
- run: ruff format --check . # … so this never runs, and you never see itYou fix the lint error, push, and get an immediate second red for formatting.
Same shape everywhere: cargo fmt --all -- --check before cargo clippy --all-targets -- -D warnings before cargo test means a formatting failure
tells you nothing about whether clippy or the tests pass.
Run every gate step locally, even after one fails. Don't &&-chain them
while diagnosing — run them separately and collect the whole set:
ruff check app tests scripts; echo "lint: $?"
ruff format --check app tests; echo "format: $?"
pytest -m "not integration"; echo "tests: $?"The corollary: after a red job, never report "only X is broken." Everything downstream of X is unmeasured until you run it.
An unpinned gating tool means the gate changes without a commit. A range like
ruff>=0.4.0 resolves to whatever shipped this morning, and a release that
widens file coverage — a formatter that starts formatting code blocks inside
Markdown, a linter that promotes a rule to default — turns every open PR red on
files nobody touched.
Two habits:
uvx ruff@0.16.4 format --check . # exactly what the runner would install
# Node: CI does `npm ci` then `npx prettier --check web` — that's the LOCKFILE's
# prettier. A bare `npx prettier` fetches the latest and flags files CI is fine
# with. Read the pinned version, then ask for it.
grep -m1 -A2 '"node_modules/prettier"' package-lock.json
npx -y prettier@3.8.3 --check webFormatting a file CI never complained about is not a fix — it's an unrelated diff caused by using a different tool than the gate.
Package managers will happily invent an environment for you, and the one they invent is not CI's.
uv run <tool> silently
creates a bare one without your dev extras, then fails with Failed to spawn: ruff — which reads like a missing dependency rather than a missing
environment.uv run re-syncs from the lockfile against your host interpreter. On a
Python newer than CI's matrix, a pinned dependency with no wheel for that
version gets built from source and fails on a compiler error that has nothing
to do with your change.[dev,web] and make install installs
[dev], the full suite errors at collection locally on an import CI has.Build it explicitly, at CI's interpreter version, with CI's extras:
uv venv .venv --python 3.12 --seed
uv pip install --python "$PWD/.venv/bin/python" -e ".[dev,web]"
.venv/bin/python -m ruff check app tests scripts
.venv/bin/python -m pytest -m "not integration"Driving the tools as .venv/bin/python -m <tool> sidesteps the re-sync entirely.
If you prefer uv run, pass --no-sync. And prefix with env -u VIRTUAL_ENV
when a shell profile exports one — otherwise the run is silently redirected into
an unrelated environment and its results mean nothing.
When you find a difference, ask where the fix belongs. A flag added to the workflow YAML fixes CI and leaves every local run diverging — so the next person hits the same confusion.
Prefer the file both sides read:
addopts in pyproject.toml, not the workflow's run:.
(Import-mode is the classic one: a source directory on sys.path shadowing an
installed compiled package is a config problem, and pinning
--import-mode=importlib in addopts fixes local and CI together.)requires-python and the linter's target-version in sync; a mismatch
means the linter applies rules for a runtime you don't support.The workflow should read as make lint / make test plus the environment. When
it contains flags the local target doesn't, that's the divergence.
Not every command in the repo is a merge blocker, and treating them as equal wastes PRs.
# Which jobs are required is a repo setting, not a file — check it
gh api repos/OWNER/REPO/branches/main/protection --jq '.required_status_checks.contexts'If CI runs the linter but not the type checker, then a pre-existing type error in
an untouched module is not blocking your PR — don't fold a speculative fix for it
into an unrelated change, and don't claim CI verifies types. The inverse matters
too: a helper target like make quality-check that runs more than CI will show
you reds that no one is gating on.
"Passes locally" is a prediction. Wait for the real result:
gh pr checks --watch
gh run view --log-failed # the failing step's output, not the summaryWhen a job is red, fix it in the same PR if the fix is feasible. If you believe it's pre-existing, prove it: check out the base commit and run the same command there. An unverified "pre-existing / out of scope" is how a base branch becomes permanently red.
Two traps in the log itself:
if: github.event.action == 'opened') is skipped
when you re-run by pushing a commit. Green-on-rerun can mean not run.Before running anything:
- [ ] Read .github/workflows/*.yml — commands, order, paths, markers, env, versions
- [ ] Local command uses CI's paths (not `.`) and CI's full marker expression
- [ ] Workflow env: block mirrored, including value shape (DB URL dialect, etc.)
Environment:
- [ ] venv created explicitly at CI's runtime version, with CI's extras
- [ ] Tools driven from that venv (`.venv/bin/python -m …` or `--no-sync`)
- [ ] `env -u VIRTUAL_ENV` when a shell profile exports one
- [ ] Gating linter/formatter/toolchain pinned; local run uses the pinned version
Running:
- [ ] Every gate step run separately — a first failure hides the rest
- [ ] Formatter check run even when the linter passed (they are different tools)
Fixing:
- [ ] Divergence fixed in shared config (manifest/addopts), not only in the workflow
- [ ] Checked which jobs are actually required before treating a red as blocking
- [ ] Waited for the real run; any red either fixed here or proven on the base commitThis repo's gate is .github/workflows/ci.yml: install ffmpeg per-OS (apt /
brew install ffmpeg-full / choco install ffmpeg), then python tests/test_all.py and python tests/test_contract.py (unittest, not pytest —
there is no marker expression to copy, but there IS an OS-conditional: a
handful of test_contract.py tests are skipIf'd on Windows because they
depend on a POSIX shell shim, not on CI's own if: gating). Read the actual
workflow file before assuming a local npm test run matches — npm test runs
both files with no OS-conditional skip logic layered on top, so on a
non-Windows machine it is already a faithful local reproduction; the gap only
shows up when debugging a Windows-specific CI failure, where the fix is to
read what skipIf actually excludes before assuming a fix applies everywhere.
Source: wdm0006/python-skills (MIT).
© kajisho5, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/reproducing-ci-locally of kajisho5/ffmpeg-skill.
Open the folder on GitHubat commit 1f7e7e3
Reproducing CI Locally next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Reproducing CI Locally this skillkajisho5/ffmpeg-skill | 1.9k | — | ~2.8k | Automated safety check: Notes | MIT | |
| Minimizing Ty Ecosystem Changesastral-sh/ruff | 50k | — | ~4.6k | Automated safety check: Pass | MIT | |
| Summarise Ecosystem Resultsastral-sh/ruff | 50k | — | ~2.2k | Automated safety check: Pass | MIT | |
| Kedro Babysitkedro-org/kedro | 11k | — | ~4k | Automated safety check: Pass | Custom licence | |
| Saleor Commit Workflowsaleor/saleor | 23k | — | ~575 | Automated safety check: Pass | BSD-3-Clause | |
| Mnemosyne Contextmnemosyne-oss/mnemosyne | 3.4k | — | ~2.6k | Automated safety check: Pass | MIT |
astral-sh/ruff
A skill your agent uses when a user says "minimize this ty ecosystem change", "reproduce this ecosystem result", "investigate a primer difference", "investigate a mypyprimer difference"…
astral-sh/ruff
A skill your agent uses when a user says "summarise ecosystem results", "summarize this ty ecosystem report", "what changed in this ecosystem run?", or asks to summarise or summarize ty ecosystem…
kedro-org/kedro
Run Kedro's local lint / format / type-check / tests on changed files (uses the project's pre-commit hooks, ruff, mypy, pytest, lint-imports, detect-secrets, Make targets — in the right venv), or…
saleor/saleor
Commits changes in the Saleor codebase and works through pre-commit hook failures from ruff, mypy, the GraphQL schema check and the migrations check.
mnemosyne-oss/mnemosyne
Load this when working on the mnemosyne memory system — its repo, sync server, memory databases, or CI.
astral-sh/ruff
A skill your agent uses when a user says "add a ty rule", "add a ty diagnostic", "write this new ty diagnostic", "change a ty error message", "review ty diagnostics", or asks to add, update, or…
kajisho5/ffmpeg-skill
Edit video and audio with local FFmpeg from natural-language requests: cut, trim, join, resize/reframe (9:16, 1:1), speed change, captions and subtitles (SRT/ASS, animated, karaoke), logos and text…
kajisho5/ffmpeg-skill
Generate GitHub Actions CI/CD pipeline configurations for automated building and testing of library and package projects.
kajisho5/ffmpeg-skill
Review a change to the ffmpeg-skill repository for the failures its own contract makes possible — a claim in a result document that is true at one layer and false at the layer a caller reads, a new…
kajisho5/ffmpeg-skill
Builds robust Python MCP (Model Context Protocol) servers with FastMCP — tool design, error contracts, event-loop-safe blocking work, subprocess/CLI wrapping, single-file vs packaged distribution…
kajisho5/ffmpeg-skill
Resolve conflicts and merges when several branches are open against one repo at the same time — the hotspot files every change must touch (registry manifests, a single version field, shared tool…
kajisho5/ffmpeg-skill
Add and review preconditions on operations that delete, overwrite, rewrite history, or resolve a caller-supplied name to a filesystem path — refusing instead of warning, placing the guard ahead of…
Works with
Categories
Run the CI gate on your machine so it agrees with the runner — deriving the exact command, paths, markers, and env from the workflow file instead of the Makefile, unblocking gate steps that…. Reproducing CI Locally is an agent skill from kajisho5/ffmpeg-skill. Run the CI gate on your machine so it agrees with the runner — deriving the exact command, paths, markers, and env from the workflow file instead of the Makefile, unblocking gate steps that short-circuit and hide the next failure, pinning the linter version CI resolves, building the interpreter/toolchain environment the runner builds, and confirming the run is green instead of explaining a red job away.
Reproducing CI Locally fits situations like: A check passes locally but fails in CI (or the reverse); A lint/format job goes red on an untouched file; setting up a local dev loop for an unfamiliar repo; before pushing a branch you expect to merge.
Run `npx skills add kajisho5/ffmpeg-skill --skill reproducing-ci-locally -a claude-code`. Or copy the skill folder (.claude/skills/reproducing-ci-locally in kajisho5/ffmpeg-skill) into .claude/skills/reproducing-ci-locally in your project. Claude Code loads it when a task matches its description.
Run `npx skills add kajisho5/ffmpeg-skill --skill reproducing-ci-locally -a codex`. Or copy the skill folder (.claude/skills/reproducing-ci-locally in kajisho5/ffmpeg-skill) into .agents/skills/reproducing-ci-locally in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add kajisho5/ffmpeg-skill --skill reproducing-ci-locally -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reproducing-ci-locally, .gemini/skills/reproducing-ci-locally, .github/skills/reproducing-ci-locally and .opencode/skills/reproducing-ci-locally in your project.
Going by SKILL.md and its folder, Reproducing CI Locally needs the command-line tools its instructions call (ruff, uv, make, pytest, python and gh). Our summary lists: Python 3; Node.js.
SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Reproducing CI Locally is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Reproducing CI Locally: Minimizing Ty Ecosystem Changes (astral-sh/ruff, 50k stars), Summarise Ecosystem Results (astral-sh/ruff, 50k stars), Kedro Babysit (kedro-org/kedro, 11k stars) and Saleor Commit Workflow (saleor/saleor, 23k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
kajisho5 (a GitHub user) maintains it in kajisho5/ffmpeg-skill, which has 1,909 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 10, 2026.
Source: kajisho5/ffmpeg-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.