agent-acceptance-gate
Use when reconciled multi-agent output needs an evidence-based PASS, CONDITIONAL PASS, or FAIL record before authorized delivery.
Use when a consequential decision has genuinely competing positions that need bounded adversarial review before a human decision.
$ npx -y skills add WenyuChiou/agent-collab-skills --skill agent-debate --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/agent-debateContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when a consequential decision has genuinely competing positions that need bounded adversarial review before a human decision.
name: agent-debate description: Use when a consequential decision has genuinely competing positions that need bounded adversarial review before a human decision.
Run a bounded adversarial review of a consequential trade-off. Debate improves the evidence visible to a decision maker; it does not establish truth by vote and does not authorize implementation.
Use debate only when:
Do not debate a factual question that can be settled by direct verification, a minor naming preference, or a decision already made by an authorized human.
the plan explicitly grants it.
Provider and model names belong to host-adapter metadata, not the public debate contract.
1. Define the decision, alternatives, known facts, disputed assumptions, evidence standard, and human decision owner. 2. Evaluate policy before every reviewer spawn. Persist a required checkpoint before continuing. 3. Give each reviewer the same evidence packet plus one position to steel-man. Reviewers are argument-only and must not modify source files. 4. After each plan-act-reflect cycle, update the `TaskCheckpoint` and evaluate policy. Stop immediately when policy says `stop`. 5. Filter missing or failed reviewer outputs, but record their status. Never invent the absent side. 6. Have the synthesizer separate agreed facts, contested claims, evidence quality, uncertainties, and falsifiable conditions that would change the recommendation. 7. Present the synthesis to the human decision owner. No implementation or canonical-memory update occurs without an explicit recorded decision.
All cycle, context, concurrency, and transcript limits come from the canonical machine-readable policy. Do not hardcode them in task packets or prose.
Produce a scratch debate record containing:
If the outcome may be useful later, emit a memory proposal. The proposal may become canonical only after an explicit human decision; resolution appends a new event and never rewrites an earlier memory record.
See `references/debate_protocol.md` for task framing.
繁體中文 · Public harness contract · 0.4 migration · 0.5 goal-slice migration Provider-neutral collaboration skills plus an optional, standard-library-first Python harness for bounded, resumable, human-authorized agent work.
Use when reconciled multi-agent output needs an evidence-based PASS, CONDITIONAL PASS, or FAIL record before authorized delivery.
Use when an agent task needs bounded context packets, checkpoint-aware compaction, a fresh-session primer, or policy-controlled child results without loading…
Use when multiple agent results must be checked for missing evidence, scope drift, contradictions, and merge conflicts before an acceptance decision.
Use when one agent must iteratively plan, act, evaluate evidence, and revise under a readable policy until acceptance, checkpoint, stop, or human escalation.
Use when a user asks to inspect coordination memory, propose a durable decision or resolution, review pending memory proposals, or apply an explicitly approved…
Use when a goal needs multiple bounded agent roles, parallel or dependent task packets, explicit scope partitions, and a provider-neutral DAG. Not for…