learn
GitHub分析历史验证结果以发现重复失败模式,并建议确定性检查规则。作为独立于主流程的辅助工具,用于从过往决策中提取经验教训,不直接修改系统状态或验证逻辑。
Trigger Scenarios
Install
npx skills add boshu2/agentops --skill learn -g -y
SKILL.md
Frontmatter
{
"name": "learn",
"consumes": [
"verdict.v2"
],
"metadata": {
"tier": "execution",
"effects": [
"write_advisory_observations"
],
"graph_root": false,
"disposition": "keep_off_path",
"capabilities": [
"analyze_verdict_collections"
],
"dependencies": [],
"canonical_status": "canonical"
},
"produces": [
"learning-observations"
],
"practices": [
"continuous-learning",
"evidence-based-engineering"
],
"context_rel": [
{
"kind": "customer-of",
"with": "validate"
}
],
"description": "Optionally analyze collections of durable verdicts for recurring evidence after the critical path. Triggers: \"learn from verdicts\", \"mine validation history\".",
"hexagonal_role": "supporting",
"user-invocable": true,
"output_contract": "advisory learning observations",
"skill_api_version": 1,
"disable-model-invocation": true
}
Learn
Learn is an optional, off-path consumer of durable verdict.v2 collections.
It may summarize recurring evidence and propose a candidate deterministic check
for later human or caller evaluation.
Prompt
Mine .agents/ao/verdicts/ for recurring patterns across the last 20
verdict.v2 records in agentops-wt/train2-c. I want candidate deterministic
checks for anything that shows up as a repeated NOT_PROVEN or FAIL cause,
with digests cited so I can trace each observation back.
It's working if
Observable in the trace, without reading the prose:
- Every observation binds a
verdict.v2digest and a finding id from.agents/ao/verdicts/. - A
NOT_PROVENorFAILverdict pair is harvested before aPASS-only pattern. - A citation that no longer resolves under
.agents/ao/verdicts/is pruned rather than paraphrased. - Output written to
.agents/scratch/learn/is labeled advisory and TTL'd, not a source of record.
Contract
Learn does not run during RPI, validate a subject, alter a verdict, mutate a plan, promote a rule, choose continuation, or mint lifecycle artifacts. Missing Learn output never changes whether a candidate is valid.
When invoked, bind every observation to verdict and finding digests, distinguish repeated objectives from repeated reviews of one objective, disclose the sample size, and stop at advisory evidence.
Inspect informative failures first, but verdict color alone establishes neither
learning value nor a missing rule. Cite the live hypothesis falsified or the
uncertainty resolved, distinguish pre-existing discovery from introduced
regression, and retain unknown causes as unknown. Repetition may justify causal
examination; it does not prove that the design was wrong or require a new gate.
The mutating-check quarantine in skills/validate/SKILL.md is an example grounded
in a specific subject-mutation incident and a NOT_PROVEN-then-PASS pair.
Knowledge is revisable. Preserve evidence and provenance when retracting an unsupported or stale belief; artifact accumulation is not a monotonic increase in truth or utility. Negative, null, and contradictory results remain visible.
A repeated finding class may support a check proposal only when causal evidence identifies a preventable defect and a concrete consumer needs that check. Name the exact behavior the check would refuse and why existing checks missed it; two sightings alone do not justify a gate. The proposal is advisory text for a human or caller to weigh; Learn never edits a gate, registry, or check script, and learning never changes a completed verdict or selects another experiment.
Prune for provenance decay: every cited artifact must still resolve — the
file exists or the verdict digest is present under .agents/ao/verdicts/. A
citation that no longer resolves gets pruned rather than paraphrased, and
confidence in a lesson that has not been reproduced since its source decayed
goes down, not sideways.
When the caller asks for a durable artifact, write the observations under
.agents/scratch/learn/ and return the path; otherwise return them inline.
The write is advisory and TTL'd — it is never a source of record, and its
absence never changes whether a candidate is valid.
Version History
-
8061085
Current 2026-09-09 05:16
新增对观察结果与判定摘要绑定的要求,明确区分重复目标与重复审查,增加样本量披露及因果证据评估规范,强化引用有效性检查。
- d9f9c50 2026-08-27 19:41
-
7b07a7d
2026-08-19 21:59
W5演进:清理死链引用,更新示例为有效规则,明确输出路径及TTL策略,强化溯源衰减处理。
- 3f402e5 2026-07-24 22:07


