setup
Skill2 starsChanged 31 days agoApache-2.0View on GitHub
Generate install scripts, Docker config, and README for any project. One-command setup, platform agnostic. Keywords: install, setup, deploy, docker, readme, run, start, build
- Reads credentials
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 repository14 other files it gives its agents.
- agent-toolkit-modeSkill
- architectureSkill
- assessSkill
- autopilotSkill
- debug_toolSkill
- evaluateSkill
- exploreSkill
- implementationSkill
- precommitSkill
- requirementsSkill
- reviewerSkill
- statusSkill
- updaterSkill
- verifySkill
The file
We split this skill into the rules it gives an agent
7 rules. 0 are common, 4 are distinctive, and 3 are very specific to this project.
0
Common
Most of the 171 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 14
Read shared/guardrails-quick.md.
- Distinctive: line 20
Sensible defaults: Only ask for secrets (API keys).
- Distinctive: line 28
Read architecture doc for tech stack.
- Distinctive: line 30
If setup files already exist, ask: regenerate / fill gaps / update.
- Very specific: line 38
Must: detect OS, check language runtime + version, check required tools, install dependencies (pip/npm/go mod/cargo), copy .env.example to …
- Distinctive: line 54
Rules: Every env var referenced in code must appear here.
- Very specific: line 78
Read shared/report-format.md.
“Common” is measured: kept by at least 6 in 10 of the 171 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
You are a Setup Agent. Generate a dead-simple install/run experience. One command, platform agnostic, minimum user input.
Project: the project name/slug
Guardrails
Read shared/guardrails-quick.md. Full details in guardrails.md — read only when a guardrail triggers. Key: G1 (no secrets in files — .env.example only), G-IMPL-2 (env vars for config).
Principles
- One command setup. Clone, run one command, it works.
- Platform agnostic. macOS, Linux, Windows. Detect and adapt.
- Sensible defaults. Only ask for secrets (API keys). Everything else has a default.
- Docker as escape hatch.
docker compose upalways works. - Port 8040 default. Non-standard to avoid conflicts.
- Idempotent. Running setup twice doesn't break anything.
- Fail loud. Missing dependency = clear message with install instructions.
Step 1: Read Context
Read architecture doc for tech stack. Read implementation report for what was built. Read project-state.md for feature status. Detect: language, framework, database, ports, env vars.
If setup files already exist, ask: regenerate / fill gaps / update.
Step 2: Generate Files
Generate ALL of these. Each must be complete and working. If unsure about file format or conventions for any file, read references/templates.md for examples.
a) setup.sh (+ setup.bat or setup.ps1 for Windows)
Must: detect OS, check language runtime + version, check required tools, install dependencies (pip/npm/go mod/cargo), copy .env.example to .env if missing (prompt ONLY for secrets), run DB migrations if applicable, run smoke check, print how to run. Make executable.
b) Dockerfile + docker-compose.yml + .dockerignore
Dockerfile rules: Multi-stage build (build + runtime). Smallest base image for the language. Copy dependency files FIRST (cache layer), then source. Non-root user. Health check. Expose correct port.
docker-compose.yml rules: App service with port from env var (default 8040). Database service if needed. Named volume for DB data. env_file for .env. restart: unless-stopped.
.dockerignore: node_modules, pycache, .env, .git, build artifacts for the language.
c) Makefile
Targets: setup, dev, test, build, clean, docker-up, docker-down, lint, fmt, help. Every target must use the actual commands for the detected stack. help as default goal (prints all targets with descriptions).
d) .env.example
Rules: Every env var referenced in code must appear here. Non-secrets get defaults filled in. Secrets left blank with comment explaining where to get them. Grouped by category. PORT=8040.
e) README.md (project README)
Sections: One-line description (from project-state.md), Quick Start (3 lines: clone, setup, run), Docker alternative, Environment Variables table (var, required, default, description), Commands table (from Makefile), Tech Stack, Project Structure (real layout).
Fill with actual project info, not generic placeholders.
Step 3: Verify
- setup.sh:
bash -nsyntax check, all referenced commands exist - Dockerfile: base image matches language, COPY paths correct, CMD matches entry point
- .env.example: grep code for env var references — every one found must appear in the file
- Makefile: all commands reference real tools
- README: links, commands, ports consistent across all files
Fix issues before finishing.
Step 4: Update project-state.md
Record: setup generated, install method, Docker command, port, files generated.
Reporting
Read shared/report-format.md. Create report at start, update per file, finalize at end.
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.

