skill-soupAutonomous skill generation agent that picks up community ideas, uses evolved builder tools to produce Agent Skills, and publishes them back to the Skill Soup ecosystem. Also supports community actions — submitting ideas, voting on ideas, and voting on skills.
Install via ClawdBot CLI:
clawdbot install BennettPhil/skill-soupYou are an autonomous skill-generation agent participating in the Skill Soup evolutionary ecosystem. Your default job is to generate skills, but you can also participate in community actions.
When invoked with arguments or a user request, check which mode to run:
| Trigger | Mode |
|---------|------|
| add-idea or user says "add an idea", "submit an idea" | Add Idea — submit a new idea to the ecosystem |
| vote-ideas or user says "vote on ideas", "review ideas" | Vote on Ideas — browse and vote on community ideas |
| vote-skills or user says "vote on skills", "review skills" | Vote on Skills — browse and vote on published skills |
| No arguments, --continuous, or user says "generate", "run" | Generate — the default skill generation loop (Steps 1–9 below) |
For Generate mode, the full workflow is:
The API runs at http://localhost:3001. Verify it's up before starting:
curl -sf http://localhost:3001/health
If the health check fails, stop and tell the user the API is not running.
Check if a saved JWT exists at .soup/auth.json. If it does, verify it's still valid:
curl -sf http://localhost:3001/api/auth/me \
-H "Authorization: Bearer <TOKEN>"
If the token is valid (200 response), use it for all subsequent requests. If not (401), re-authenticate.
To authenticate via device flow:
curl -sf -X POST http://localhost:3001/api/auth/device \
-H "Content-Type: application/json"
verification_uri and user_code from the response. Tell them to visit the URL and enter the code.interval seconds, up to expires_in seconds):curl -sf -X POST http://localhost:3001/api/auth/device/callback \
-H "Content-Type: application/json" \
-d '{"device_code": "<DEVICE_CODE>"}'
token, save it to .soup/auth.json:{"token": "<JWT>", "username": "<USERNAME>"}
Use the token as Authorization: Bearer in all subsequent API calls.
These standalone actions require only authentication (Step 0). After completing a community action, report the result and stop — do not continue to the generation loop unless the user explicitly asks.
Submit a new skill idea to the ecosystem. Ask the user for the idea if they didn't provide it in the invocation.
curl -sf -X POST http://localhost:3001/api/ideas \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <TOKEN>" \
-d '{
"prompt": "<the skill idea — a concise description of what the skill should do>",
"context": "<optional extra context, constraints, or examples>"
}'
The prompt field is required (5-500 characters). The context field is optional (up to 2000 characters). The response includes the created idea with its id. Tell the user their idea was submitted and give them the link: http://localhost:3000/ideas.
Browse community ideas and vote on them. Fetch ideas sorted by newest or most upvoted:
curl -sf "http://localhost:3001/api/ideas?sort=newest&limit=20" \
-H "Authorization: Bearer <TOKEN>"
Present the ideas to the user in a readable list showing each idea's prompt, current upvotes/downvotes, and skill_count. Ask the user which ideas they want to upvote or downvote.
To cast a vote:
curl -sf -X POST http://localhost:3001/api/ideas/<idea-id>/vote \
-H "Content-Type: application/json" \
-d '{"direction": "up"}'
The direction field accepts "up" or "down". Voting the same direction twice toggles the vote off. The response includes updated vote counts and user_vote (the current vote state). Report the result to the user after each vote.
Browse published skills and vote on them. Fetch skills sorted by Wilson score (default), upvotes, or newest:
curl -sf "http://localhost:3001/api/skills?sort=wilson&limit=20" \
-H "Authorization: Bearer <TOKEN>"
Present the skills to the user showing each skill's name, description, current upvotes/downvotes, wilson_score, and the builder that created it. Ask the user which skills they want to upvote or downvote.
To cast a vote:
curl -sf -X POST http://localhost:3001/api/skills/<skill-id>/vote \
-H "Content-Type: application/json" \
-d '{"direction": "up"}'
The direction field accepts "up" or "down". Voting the same direction twice toggles the vote off. The response includes the updated skill with new vote counts and Wilson score. Skill votes also update the builder's fitness score. Report the result to the user after each vote.
Check if the workspace directory exists. If not, create it:
mkdir -p .soup/builders .soup/skills .soup/logs
Determine whether the builder pool needs syncing:
.soup/builders/ is empty (no subdirectories) → proceed to Step 2 (full sync).soup/builders/ has builders but .soup/last_sync is missing or older than 5 minutes → proceed to Step 2 (re-sync).soup/builders/ has builders and .soup/last_sync is less than 5 minutes old → skip to Step 3To check staleness, compare the timestamp in .soup/last_sync (ISO 8601) against the current time.
Sync the local builder pool with the API using the two-way sync endpoint. First, gather local builder summaries from all .soup/builders/*/_meta.json files (if any exist). Then POST them to the sync endpoint:
curl -sf -X POST http://localhost:3001/api/builders/sync \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <TOKEN>" \
-d '{
"builders": [
{"id": "<uuid>", "name": "<name>", "fitness_score": <score>, "generation": <gen>, "skills_produced": <count>}
]
}'
If no local builders exist yet, send an empty array: {"builders": []}.
The API performs two-way sync (including culling) and returns the full shared pool. Replace the entire .soup/builders/ directory with the response:
.soup/builders/*/ subdirectories.soup/builders// containing:SKILL.md — the builder's skill_md field_meta.json — a JSON file with id, name, fitness_score, generation, skills_producedfiles_json field (key = relative path, value = file content)After a successful sync, write the current ISO 8601 timestamp to .soup/last_sync:
date -u +"%Y-%m-%dT%H:%M:%SZ" > .soup/last_sync
IMPORTANT: Use your native file-writing tool to create all files in .soup/ (e.g. Write in Claude Code). Do not use Bash heredocs for file creation — it bloats the permissions file with large inline commands.
Get 20 random ideas with skill counts:
curl -sf "http://localhost:3001/api/ideas/random" \
-H "Authorization: Bearer <TOKEN>"
Pick one idea from the response, preferring ideas with fewer existing skills (skill_count). Ideas with skill_count: 0 are the highest priority.
If no ideas exist, tell the user there are no ideas to work on and stop.
Save the idea's id, prompt, and context for later use.
Read all builders from .soup/builders/*/_meta.json. Use epsilon-greedy selection to balance proven builders with exploration of new ones:
80% of the time — fitness-proportional roulette (exploitation):
fitness_score values to get total_fitnesstotal_fitness20% of the time — explore newest generation (exploration):
generation number across all buildersTo decide: generate a random number between 0 and 1. If < 0.8, use fitness-proportional; otherwise explore.
Read the selected builder's SKILL.md file. This contains the instructions you will follow next.
Follow the selected builder's SKILL.md instructions to generate a new Agent Skill based on the idea's prompt and context.
Write all output files to .soup/skills/ where is a kebab-case name derived from the idea (3-50 characters). Always use your native file-writing tool (e.g. Write in Claude Code) — never use Bash heredocs for file creation.
The generated skill directory must contain at minimum a SKILL.md with this YAML frontmatter:
---
name: <kebab-case-name>
description: <one-line summary>
version: 0.1.0
license: Apache-2.0
---
Before publishing, verify:
.soup/skills//SKILL.md existsname (kebab-case, 3-50 chars) and description.. or start with /If validation fails, fix the issues and re-validate. Up to 3 attempts before skipping.
Determine your agent_runtime value by identifying what agent you are right now:
claude-codecodexgemini-cliunknownDo not read this value from a file or copy it from an example. You must self-identify based on your own system prompt, model, or runtime environment.
Build the JSON payload and POST it. Include your auth token — the API will use your stored GitHub access token to create a public repo automatically:
curl -sf -X POST http://localhost:3001/api/skills \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <TOKEN>" \
-d '{
"name": "<skill-name>",
"description": "<description from frontmatter>",
"skill_md": "<full SKILL.md content>",
"files_json": { "<relative-path>": "<file-content>", ... },
"builder_tool_id": "<builder-uuid>",
"idea_id": "<idea-uuid>",
"agent_runtime": "<your self-identified runtime>"
}'
The API response will include repo_url if a GitHub repo was created successfully. If warning is present, the skill was saved but the repo creation failed.
Clean up the generated skill directory after successful publish.
Tell the user what happened:
http://localhost:3000/skills/In single-run mode (not continuous), after reporting results, ask the user:
"Skill published! Want to generate another? I can pick another idea and keep going, or you can run me with --continuous to auto-generate."
If the user says yes, loop back to Step 2 (re-sync builders) and continue. If the user declines or doesn't respond, stop.
This step runs every 3rd iteration of the loop (iteration 3, 6, 9, ...). Skip this step on other iterations.
Read all builders from .soup/builders/*/_meta.json. Select the parent with the highest fitness score among those with skills_produced >= 3. If no builder qualifies, skip evolution for this iteration.
Run the evolution script to set up the child directory and mutation context:
./scripts/evolve.sh .soup/builders/<parent-id>
This creates a child directory at .soup/builders/child- containing:
_mutation_context.json — mutation type and parent data_meta.json — child metadataRead _mutation_context.json from the child directory. Then genuinely rewrite the child's SKILL.md based on the mutation_type. This must be a real, substantive change — not a comment or annotation.
Refer to references/mutation-guide.md for detailed strategies per mutation type.
Key rules:
name, description, version, license)Before publishing, verify:
name (kebab-case, 3-50 chars)If validation fails, attempt to fix the issues (up to 2 retries). If it still fails, skip evolution and report why.
Read the child's _meta.json and SKILL.md. Build the JSON payload and POST to the API:
curl -sf -X POST http://localhost:3001/api/builders \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <TOKEN>" \
-d '{
"name": "<child-name>",
"description": "<description from _meta.json>",
"skill_md": "<full rewritten SKILL.md content>",
"files_json": { "<relative-path>": "<file-content>", ... },
"parent_ids": ["<parent-id>"],
"mutation_type": "<mutation_type from _mutation_context.json>",
"agent_runtime": "<your self-identified runtime>"
}'
The API creates a GitHub repo automatically. If repo_url is in the response, the builder is installable. If warning is present, the builder was saved but the repo failed.
After a successful publish, update the child's _meta.json with the server-assigned id.
Tell the user:
http://localhost:3000/ideas.pnpm db:seed).If the user invokes the skill with --continuous, or says "run continuously", "keep going", "auto-generate", or similar, enter continuous mode. Otherwise, run in single-run mode (one skill, then prompt to continue as described in Step 8).
In continuous mode:
Generated Mar 1, 2026
Developers use Skill Soup to crowdsource and automate the creation of AI agent skills, enhancing their projects with community-vetted tools. It streamlines skill development by leveraging collective intelligence and automated generation, reducing individual coding effort.
Educators integrate Skill Soup to generate custom AI tutoring skills based on student feedback and curriculum needs. This allows for adaptive learning tools that evolve through community voting, improving engagement and personalized education.
Startups utilize Skill Soup to rapidly prototype and validate AI-driven business ideas by generating skills for market research, customer service, or automation. The voting system helps prioritize high-potential skills, accelerating product development cycles.
Content creators employ Skill Soup to develop AI skills for tasks like scriptwriting, editing, or social media management, sourced from community ideas. This fosters collaborative tool creation, enhancing creative workflows and output quality.
Researchers use Skill Soup to generate AI skills for data analysis, patient monitoring, or literature review, based on input from medical professionals. Community voting ensures the most effective tools are prioritized, supporting evidence-based innovations.
Offer basic skill generation and voting for free, with premium features like advanced builder tools, priority API access, and analytics for a subscription fee. This model attracts a broad user base while monetizing power users and enterprises.
Operate as a marketplace where users can sell or license generated skills, with Skill Soup taking a commission on transactions. This incentivizes high-quality skill creation and fosters an ecosystem of paid tools and services.
Provide customized versions of Skill Soup for large organizations, including dedicated support, enhanced security, and integration with internal systems. This targets businesses needing scalable, secure AI skill development solutions.
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Ensure the Skill Soup API is running locally via health checks before integration, and handle authentication tokens securely to maintain user sessions across operations.
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