setup
Skill25 starsChanged 7 days agoMITView on GitHub
Configure aigent-OS identity, priorities, authority, projects, people, and decision logic. Use when running setup, reconfiguring settings, or changing authority levels.
191 other projects use a version of this.
Adopted by
Most recently taken up by
- hydra-db/hydradb-claude-codetheir own version, first seen Nov 8, 2026
- WALKERKILLER/Look-Tongji-Notestheir own version, first seen Nov 8, 2026
- steerlabs/opensteertheir own version, first seen Nov 8, 2026
- ansvisor/ansvisortheir own version, first seen Nov 8, 2026
- dsifry/metaswarmtheir own version, first seen Nov 8, 2026
- anombyte93/prd-taskmastertheir 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★ 35ksame 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.
In this repository71 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- docs/llms.txtllms.txt
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- The first 60 shown.
The file
Show its rules and text
We split this skill into the rules it gives an agent
13 rules. 0 are common, 5 are distinctive, and 8 are very specific to this project.
0
Common
Most of the 170 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
8
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 15
If state is missing or not ready, route through /start unless the operator explicitly requested advanced setup.
- Very specific: line 16
If state is ready, ask which configuration area needs revision rather than replaying the entire interview.
- Distinctive: line 17
Never detect setup state by searching for placeholder prose in a Markdown file.
- Very specific: line 19
Before writing, set status: setup-in-progress while preserving any prior completedAt.
- Distinctive: line 23
Ask one question at a time and write each completed section immediately.
- Very specific: line 27
Ask for the operator's role, responsibilities, preferred collaboration style, and risk posture.
- Very specific: line 31
Ask for the top two or three active priorities, the most urgent outcome, operating mode, and blockers.
- Very specific: line 35
Ask what the AI may handle autonomously, what needs confirmation, what is human-only, and whether spending has an escalation threshold.
- Very specific: line 39
Ask what makes the operator accept or reject opportunities, their active-work limit, and their most common time trap.
- Distinctive: line 47
Ask whether any specialized agents are useful now.
- Distinctive: line 51
After all requested sections are durably written:
- Very specific: line 65
Write .aigent/first-run-done for compatibility with older installs.
- Distinctive: line 68
Do not mark the installation ready when required writes failed.
“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
aigent-OS setup and reconfiguration
/start owns the day-one onboarding arc. /setup is the deeper configuration flow and may also be used later to revise one section.
Entry behavior
Read .aigent/state.json first.
- If state is missing or not
ready, route through/startunless the operator explicitly requested advanced setup. - If state is
ready, ask which configuration area needs revision rather than replaying the entire interview. - Never detect setup state by searching for placeholder prose in a Markdown file.
Before writing, set status: setup-in-progress while preserving any prior completedAt. On interruption, the next /start or /setup should resume from the last durably completed section.
Interview
Ask one question at a time and write each completed section immediately.
1. Identity
Ask for the operator's role, responsibilities, preferred collaboration style, and risk posture. Update system/00_identity.md without replacing framework-owned doctrine.
2. Priorities
Ask for the top two or three active priorities, the most urgent outcome, operating mode, and blockers. Update vault/memory/ACTIVE_PRIORITIES.md.
3. Authority boundaries
Ask what the AI may handle autonomously, what needs confirmation, what is human-only, and whether spending has an escalation threshold. Update system/12_authority_matrix.md.
4. Decision logic
Ask what makes the operator accept or reject opportunities, their active-work limit, and their most common time trap. Update system/14_decision_framework.md.
5. Projects and people
For each active project, capture purpose, current state, priority, next action, and relevant people. Create or update notes under vault/projects/ and vault/people/, then connect them from active priorities with wikilinks.
6. Specialist agents
Ask whether any specialized agents are useful now. For each accepted agent, capture name, scope, tools, model tier, escalation boundary, and success criteria. Store the definition in vault/agents/ with valid name: and tools: frontmatter so the installer can register it in .claude/agents/.
Completion
After all requested sections are durably written:
- Summarize exactly what changed.
- Append an idempotent setup entry to
vault/memory/SESSION_LOG.md. - Set
.aigent/state.jsonto:
{
"schemaVersion": 1,
"status": "ready",
"completedAt": "<ISO-8601 timestamp>"
}- Write
.aigent/first-run-donefor compatibility with older installs. - Teach or remind the operator of
/open, normal work, and/close.
Do not mark the installation ready when required writes failed.
Rules
- One section at a time.
- Adapt to information already supplied.
- Mirror the operator's language without inventing details.
- Preserve user-authored content and make precise edits.
- Sections may be deferred explicitly.
- Reconfiguration must not erase unrelated state.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
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.

