Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Verification methodology and gate checklist for the tdmcp Connectors Directory submission — run the docs build, build and inspect the .mcpb bundle, sweep for stale .dxt references, and cross-check the form-answer draft against the real requirements. Use to validate the submission package before a human submits, by executing commands and quoting evidence, not by trusting that work was done.
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See how to installReview the instructions the agent will receive before you install.
The cost of a miss is a ~2-week rejection cycle. So every gate is checked by running something and quoting the output, never by reading a builder's claim. "Looks complete" is not a result; a command transcript is.
Produce a table gate | PASS/FAIL | evidence. Gates:
| Gate | How to verify |
|---|---|
| Privacy page exists + linked | Open the page file(s); confirm the nav entry in docs/.vitepress/config.ts points to its clean URL. Confirm the page actually states the data-handling story (not a stub). |
| Docs build | npm run docs:build exits 0. VitePress fails on dead internal links, so this also catches a bad nav link. |
| Bundle builds | npm run build then npm run build:mcpb (or the renamed script). Confirm tdmcp.mcpb is emitted. |
| Bundle is valid | unzip -l tdmcp.mcpb shows manifest.json at root + dist/. If npx --yes @anthropic-ai/mcpb validate exists, run it on the manifest and capture the result. |
| No stale refs | grep -rn "\.dxt|build:dxt" docs/ scripts/ README.md package.json .github/ 2>/dev/null (exclude dist/, node_modules/). Every hit must be an intentional legacy note. |
| Annotations intact | `grep -rEo "readOnlyHint |
| Form completeness | Every field in 00_submission-spec.md's field map has an answer in 02_form-answers.md or an explicit NEEDS HUMAN INPUT. List the human inputs. |
| Manifest sane | node -e "JSON.parse(require('fs').readFileSync('dxt/manifest.json'))" parses; manifest_version, name, version, server.entry_point present. |
Write _workspace/03_qa-report.md:
NEEDS HUMAN INPUT (support email,
privacy contact, test account, new release to publish the .mcpb asset).general-purpose capability, not a
read-only profile.02_form-answers.md must resolve to the page docs-author
actually created; the tool list in the form must match src/tools/**.No reviews yet. Tell others what you thought.
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Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.
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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
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agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
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