Search the workflow dataset for best practices from past projects, and help users contribute new run records. Each dataset entry is a real orchestrate-run: domain, stack, architecture, workflows, outcome, lessons. Search it before designing a project so new work starts from accumulated experience. Use when: "search the dataset", "find similar projects", "what worked for X", "contribute to the dataset", "add a dataset entry", "best practices for X".
How this skill is triggered — by the user, by Claude, or both
Slash command
/claude-workflow-plugin:datasetThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
The plugin ships a dataset of real orchestrate-run records under `dataset/`.
The plugin ships a dataset of real orchestrate-run records under dataset/.
This skill searches it and helps users grow it. The richer the dataset, the
better every future orchestrate run starts.
Two interfaces over the same scoring (dataset/lib.ts):
The plugin registers the dataset-server MCP server. Call its tools:
dataset_search — args: domain, stack[], archetype, keywords[],
limit. Returns ranked entries with their lessons.dataset_get — args: id. Returns one full entry.dataset_stats — no args. Returns entry/domain/archetype counts.If the MCP server is not connected, fall back to the CLI.
bun run dataset/search.ts '{"domain":"rest-api","stack":["bun"],"archetype":"verified-swarm","keywords":["auth"],"limit":5}'
domain + stack, surface
the architecture and lessons of similar past projects to the user.domain to see which archetype each
phase used and how many rounds it took to converge.keywords for entries whose
pitfalls describe the same trap.Always tell the user which entries informed a recommendation — cite the entry
id. Treat lessons as evidence, not law: an entry reflects one project.
Run this after a real project ships (orchestrated or hand-built).
dataset/README.md and dataset/schema.json.dataset/entries/<id>.json. Required: id, domain, summary,
stack, architecture, workflows, outcome, lessons, contributor,
contributedAt. Be honest about outcome and pitfalls — a failed run with
a clear lesson is as valuable as a clean one.bun run dataset/validate.ts — must print N/N entries valid..github/ISSUE_TEMPLATE/dataset-contribution.yml) for a maintainer to add.To help a user contribute: interview them for each required field, write the JSON file, run the validator, and show them the result before opening the PR.
orchestrate skill — Steps 4 (architecture) and 5
(workflow synthesis) should search it first.npx claudepluginhub xirothedev/claude-workflow-plugin --plugin claude-workflow-pluginGuides creation, editing, and verification of skills for AI coding agents using test-driven development with subagent scenarios. Use when authoring or debugging skills.