setup
Skill1 starsChanged 32 days agoMITView on GitHub
Pick ready-made rules to switch on
191 other projects use a version of this.
Adopted by
Most recently taken up by
- finolabs/vibecodetheir own version, first seen Nov 15, 2026
- quickchatai/quickreviewtheir own version, first seen Nov 15, 2026
- tomw1808/flash-agentstheir own version, first seen Nov 15, 2026
- felipeam86/pipe-skillstheir own version, first seen Nov 15, 2026
- oss-invisible/playwright_mcptheir own version, first seen Nov 15, 2026
- hydra-db/hydradb-claude-codetheir own version, first seen Nov 8, 2026
Used with
Projects with it also use add-voice-transcription, add-discord and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
juancruzmunozalbeloSkilladd-voice-transcription
Add voice message transcription to NanoClaw using OpenAI's Whisper API. Automatically transcribes WhatsApp voice notes so the agent can read and respond to them.
Also in 5 projects that use this
MicrosoftSkilladd-discord
Add Discord bot channel integration via Chat SDK.
Also in 11 projects that use this
MicrosoftSkilladd-slack
Add Slack channel integration via Chat SDK.
Also in 11 projects that use this
juancruzmunozalbeloSkilladd-telegram-swarm
Add Agent Swarm (Teams) support to Telegram. Each subagent gets its own bot identity in the group. Requires Telegram channel to be set up first (use /add-telegram). Triggers on "agent swarm", "agent teams telegram", "telegram swarm", "bot pool".
Also in 7 projects that use this
- +8 more from microsoft
Other versions191 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 191
- anthropics/knowledge-work-plugins★ 36ksame name
- garrytan/gbrain★ 32ksame name
- gavrielc/nanoclaw★ 31ksame name
- nanocoai/nanoclaw★ 31ksame name
- qwibitai/nanoclaw★ 31ksame name
- Q00/ouroboros★ 6.3ksame name
- pytorch/executorch★ 5.2ksame name
- agenticnotetaking/arscontexta★ 3.5ksame name
- aws/agent-toolkit-for-aws★ 3.4ksame name
- spotify/portal-ai-plugins★ 2.8ksame name
181 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
We split this skill into the rules it gives an agent
7 rules. 0 are common, 1 is distinctive, and 6 are very specific to this project.
0
Common
Most of the 170 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
6
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 16
List the library: run agentltl library --json.
- Very specific: line 24
Let the user choose: Use the AskUserQuestion tool with multiSelect: true.
- Distinctive: line 33
If there are more entries than fit, ask in several rounds.
- Very specific: line 36
Ask about strictness: only if the user wants it.
- Very specific: line 47
Check the result: run agentltl validate. Then show the user the rules now in force, with each rule's mode and one line on what it does.
- Very specific: line 49
If a chosen rule depends on the project, say so.
- Very specific: line 54
Offer to scan memory: run agentltl memory scan --json.
“Common” is measured: kept by at least 6 in 10 of the 170 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Choosing packaged rules
The plugin ships a library of tested rules. Switching one on adds its name to the use: list
of AGENTLTL.yaml; the rule itself stays in the plugin and gets fixes with plugin updates.
Arguments: $ARGUMENTS (--user means rules for every project, in ~/.claude/AGENTLTL.yaml).
Steps
- List the library: run
agentltl library --json. Each entry has aname, asummary,tags,in_use(already on in a file that applies here) and its rule ids. - Ask where the rules go, unless
--userwas given: this project (AGENTLTL.yamlat the project root) or every project (~/.claude/AGENTLTL.yaml). Rules for one repository's workflow (tests, deploys) usually belong to the project; personal habits (no Claude co-author, subagents on Sonnet) to every project. - Let the user choose. Use the AskUserQuestion tool with
multiSelect: true. It takes at most 4 questions per call, and at most 4 options per question.- Group the entries by theme using their tags, for example "Git safety", "Files and secrets", or "Workflow and cost".
- Each option's label is the entry's
name, and its description is thesummary. - Offer a bundle (an entry tagged
bundle, such asdevops-secrets, or a theme:theme-release-safety,theme-data-safety,theme-budget,theme-research,theme-human-in-the-loop) as one option that switches on all the entries it lists. - Mark entries already on with "(on)" in the description. Tell the user that unticking one switches it off.
- If there are more entries than fit, ask in several rounds.
- Without AskUserQuestion, show a numbered list and ask for the numbers.
- Ask about strictness only if the user wants it. Every entry has a sensible default
mode. To change it, use
agentltl use NAME --mode warn. The modes are block, warn, ask, retry, stop and log; see the/agentltl:rulesskill's reference.md. Apply the choices, adding
--userfor every project:agentltl use NAME...for the newly ticked entries;agentltl unuse NAME...for the ones the user unticked.
These commands edit only the
use:list and keep the rest of the file. They create the file if it is missing.- Check the result: run
agentltl validate. Then show the user the rules now in force, with each rule's mode and one line on what it does.- If a chosen rule depends on the project, say so. For example,
tests-before-pushknows common test runners (pytest, npm test, cargo test, make test...). If the project tests differently, offer to write a project rule with the same id: it replaces the packaged one. agentltl library NAMEshows a rule's YAML in full.
- If a chosen rule depends on the project, say so. For example,
- Offer to scan memory: run
agentltl memory scan --json. If itscounts.candidatesis above 0, offer "Scan CLAUDE.md and memory for rules (N statements in M files)". If the user accepts, follow the import skill from its step 2, reusing that scan. Instructions already in memory then become rules that are enforced. Offer the status line, once per machine. Claude Code shows nothing a plugin prints at startup, so the status line is where the user sees that AgentLTL is on:
AgentLTL ● 4 rules · 2 block · 1 ask · 1 warn. Check~/.claude/settings.json:- It has no
statusLine: ask "Show AgentLTL and the number of rules in force in the status line?" If yes, runagentltl statusline --install. It changes only that key. - It already shows AgentLTL: say so and skip this step.
- It has another status line: don't replace it. Show the line the install prints, which
adds AgentLTL's line to the user's own script, and replace it with
--forceonly if the user asks.
The line appears on the next prompt; no restart is needed.
- It has no
- Offer custom rules: for anything the library and memory don't cover, use the
/agentltl:rulesskill to write a rule from the user's own words.
Changes apply from the next tool call. No restart is needed.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

