docs(workflows): clarify evidence-free acceptance criteria

README.md

@@ -322,6 +322,8 @@ acceptance: {
 
 条件缺失、格式错误或被拒绝时，调用返回 `ok: false`，但原始输出与 ledger 仍保留。OpenPI 不会暗中再启动 reviewer、Shell 或额外 Judge 模型。
 
+未设置 `requiredEvidence` 的 criterion 是对 `description` 的自我声明，不是有证据约束的验收门禁；需要 evidence-backed gate 时，必须声明所需证据标签。
+
 ### Worktree Handoff
 
 Workflow 在清理隔离 checkout 前原子保存有界 Handoff Manifest：tracked binary patch、stat、branch/HEAD、untracked/ignored 清单与 cleanup receipt。状态不明就保留现场，不自动 merge、apply 或强删。

skills/workflows/REFERENCE.md

@@ -18,7 +18,7 @@ Useful options include `agent_type`, `label`, `phase`, `schema`, `acceptance`, `
 
 - Prefer a matching `agent_type`. Model precedence is explicit model/provider, type file, configured built-in role, then parent. Effort precedence is explicit effort, type default, then parent.
 - `schema` validates structured output. Use it whenever later workflow logic branches on fields.
-- `acceptance: { criteria: [{ id, description, requiredEvidence?: string[] }] }` requires the same child to return an evidence ledger. An invocation accepts 1–32 criteria; each criterion has a 1–500 character human-readable `description` and an optional `requiredEvidence` array of at most 16 concise string labels (up to 120 characters each). The child must return exact matching labels in `acceptance.criteria[].evidence`. Missing, malformed, or rejected criteria make `ok:false` while preserving output and evidence.
+- `acceptance: { criteria: [{ id, description, requiredEvidence?: string[] }] }` requires the same child to return an evidence ledger. An invocation accepts 1–32 criteria; each criterion has a 1–500 character human-readable `description` and an optional `requiredEvidence` array of at most 16 concise string labels (up to 120 characters each). The child must return exact matching labels in `acceptance.criteria[].evidence`. A criterion without `requiredEvidence` is an attestation of its description, not an evidence-backed gate; criteria that need evidence-backed acceptance must declare the required labels. Missing, malformed, or rejected criteria make `ok:false` while preserving output and evidence.
 - `operator: "name"` reuses one in-memory child Session for serialized follow-ups inside the same run. Its model, role/tools, effort, structured mode, and cwd are frozen by the first activation. Operators cannot use per-call worktrees or replay, and do not survive restarts.
 - `inputs: [ref, ...]` accepts successful opaque refs from the same workflow run only. Each conclusion is bounded to 16 KiB and total injected input to 48 KiB. The total budget is fairly distributed, so a large fan-out cannot starve later results merely because of order; partial projections are labeled. Full successful child results remain in the run's `agent-results/` artifacts. Inputs are marked as untrusted data; the resulting graph is observability, not scheduling authority.
 - Fair projection preserves the head and tail of every partial result and names its run-relative `agent-results/agent-N.json` audit artifact. That path is provenance for the parent/operator, not a child-readable handle. Fair presence is not proof of full evidence coverage: for large fan-out, group source refs into local Report agents, then pass only their refs to a global Report. The workflow script—not Runtime—must state planned, selected, covered, failed, and deferred counts.