agent-watchdog
Use when asked to watch, babysit, audit, review, compare, or fix another agent's work from a…
Use when asked to compare, cross-review, merge, judge, choose, or arbitrate competing plans from multiple agents such as Codex and Claude Code; when given two or more proposed plans, session IDs, transcripts, plan documents, PR descriptions, or pasted strategies; or when the
$ npx -y skills add BuilderIO/skills --skill plan-arbiter --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/plan-arbiterContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when asked to compare, cross-review, merge, judge, choose, or arbitrate competing plans from multiple agents such as Codex and Claude Code; when given two or more proposed plans, session IDs, transcripts, plan documents, PR descriptions, or pasted strategies; or when the
name: plan-arbiter description: Use when asked to compare, cross-review, merge, judge, choose, or arbitrate competing plans from multiple agents such as Codex and Claude Code; when given two or more proposed plans, session IDs, transcripts, plan documents, PR descriptions, or pasted strategies; or when the user wants one recommended execution plan after agents review each other's proposals.
Turn competing plans into one executable direction. Preserve the best ideas, reject weak assumptions, and produce a clear handoff instead of a blended mush.
1. Collect the source plans. 2. Normalize each plan into comparable claims. 3. Cross-review the plans against each other and the real codebase or task context. 4. Choose a winner, merge a better hybrid, or send the plans back for revision. 5. Produce one execution handoff with verification gates and rejected alternatives.
Planning is read-only unless the user explicitly asks you to implement after the decision.
Accept plans as pasted text, local files, session IDs, transcript paths, PRs, comments, visual-plan links, or chat history. Resolve the original artifacts when possible so you can see prompt changes and assumptions that may be missing from a final summary.
If a plan is still being written and the user asked you to wait, monitor it until it is done or blocked. If a plan cannot be resolved, continue with the available plan text and mark the missing source as a risk.
For each plan, extract:
Do not reward verbosity. Prefer plans that are concrete, grounded in real code, and honest about tradeoffs.
Review each plan as if another capable agent wrote it:
when those are relevant and available.
unnecessary scope, and hard-to-reverse decisions.
while another has the better migration or validation path.
be the right choice for implementation even when another model produced the best critique.
Use subagents for independent review when the plans are large, the codebase is wide, or the decision would benefit from separate technical and product passes.
Choose one of three outcomes:
key constraint or depend on an unresolved decision.
Use this tie-break order:
1. Correctness and fit to the user's request. 2. Grounding in real files, APIs, tests, data, and UI behavior. 3. Simpler first implementation that does not block the intended future. 4. Better validation and rollback story. 5. Lower token/time cost for execution once quality is acceptable.
Return a compact decision memo:
Decision - Adopt Plan A / Hybrid / Revise first. Why - The deciding evidence and tradeoffs. Execution Plan - Ordered steps with files or surfaces to touch. Borrowed From Other Plans - Useful pieces kept from non-winning plans. Rejected - Ideas intentionally not taking, with reasons. Verification - Tests, browser checks, screenshots, CI, review, or deploy checks needed. Executor Recommendation - Which agent/model should implement and why.
When the user already asked for execution and the chosen path is clear, proceed with the selected plan after reporting the decision briefly. Otherwise stop at the handoff and ask for approval.
Small, composable skills for your favorite agent.
Repo: BuilderIO/skills
Use when asked to watch, babysit, audit, review, compare, or fix another agent's work from a…
Open and operate Agent-Native workspace apps through Dispatch MCP, with inline app surfaces,…
Use when running Claude Fable on codebase-heavy or token-heavy work and the user wants Fable…
Apply the same orchestration as `/efficient-fable` to any high-cost frontier model: delegate…
Experimental workflow for babysitting one explicitly authorized pull or merge request. Use to…
Experimental workflow for collecting and triaging product feedback, product telemetry,…