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OpenClaw 官方免费在 GitHub 公开中文介绍

knowledge-recall

搜索已保存的 Knowledge 页面,依据相关记录回答有关资料、会议、人物或项目的问题,并附上来源引用。

原文查看原文说明

Find and answer from saved Knowledge vault pages with source citations. Use for questions about stored documents, meetings, people, or projects; not for recalling conversation history or searching the web.

openclaw/openclaw星标 393,141(GitHub 393,141 + cccskills 0)

实测评分 未实测

查看安装方法

适用场景

  • 从已保存资料中查找答案
  • 核对会议记录中的决定
  • 追溯项目历程
  • 区分记录日期与事件日期

中文介绍

功能

搜索已保存的 Knowledge 页面,读取相关记录,并根据检索到的内容组织答案。可回答有关资料、会议、人物和项目的问题,同时标明信息来源。综合多条记录时,会区分摘要与不同说法,并查看历史,避免把旧信息当作当前情况。回答日期或时间段问题时,可以分开查明事件发生时间和记录保存时间。

适用场景

需要从已保存的知识中查找依据、核对会议决定或追溯项目历程时,可以使用此技能。它不用于回忆对话历史,也不用于网页搜索。

使用示例

  • “请从已保存的会议记录中整理决定,并附上来源。”
  • “请告诉我关于这个项目记录的最新信息。”
  • “请分别查明这件事发生的日期和记录日期。”

注意事项

Knowledge 的搜索和读取仅限只读。没有检索到结果,并不能证明知识库中不存在相关信息。若要保存新信息以供日后使用,请另行使用 knowledge-capture 技能。

本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。

文档检查

AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。

安全性发送数据、删除文件、执行命令等是否有说明
A良好资料注明流程只读,并要求不要仅凭无结果断定信息不存在。
安装难易度所需工具和 API 密钥是否少且有说明
B部分不足资料提到了 Knowledge 工具和 Control UI,但未说明安装要求。

不计入评分。 由 AI(OpenAI Codex)于 2026年10月26日 评估。仅供参考,安装前请同时查看原文。

如果您认为评估有误,请申请复核

请写明哪一项有误以及原因。无需登录。我们会对照 SKILL.md 重新评估,并在此处更新结果。

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

包含的文件(12)

  • SKILL.md5.0 KB
  • references/assertions.md4.6 KB
  • references/conventions.md14.3 KB
  • references/identity.md4.8 KB
  • references/meeting-entity-example.md6.8 KB
  • references/profiles.md2.8 KB
  • references/publish.md3.0 KB
  • references/recovery.md2.0 KB
  • references/setup.md1.7 KB
  • references/sources.md3.0 KB
  • references/verify.md2.7 KB
  • references/writing.md1.9 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Recall saved knowledge

Read shared conventions. This workflow is read-only.

  1. Search with knowledge_grep({query}), including for named people, projects and pages whose exact stored identity is not already known: literal words, all by default; try a concise variant, any, or phrase when useful. No embeddings, regex, graph traversal or server-side synthesis is available. Narrow by ontology type/kind when appropriate; use knowledge_records and pagination for an inventory, not a ranked search pretending to be exhaustive.
  2. Use knowledge_lookup({query}) only for an already-known exact record ID, full title or declared alias. It does not perform keyword search. If it returns missing, fall back to knowledge_grep before concluding no relevant record exists. Preserve ambiguous as ambiguity and inspect candidates rather than choosing one.
  3. Inspect relevant hits with knowledge_record. Read enough context to support the answer. Compact metadata is included by default; request includeEvidence: true for source locators, excerpts and attribution support, and metadataView: "full" for arbitrary domain fields. Connections default to compact identities/endpoints/uncertainty; request view: "full" only for richer metadata/evidence, and includeCards: true with full view for prose. Follow body/evidence/connection pagination as needed. Compare the hit's citation hash/revision to the readback. Restart on changes rather than combine incompatible revisions. Use includeReferences only for declared structured connections; prose links do not populate that list automatically.
  4. Answer from the retrieved passages. In Control UI chat, cite readable titles linked to the dedicated Knowledge record page using the shared conventions' chat-link contract. Retain relevant source locators and propagate original evidence, not only the generated summary. Label synthesis and disagreements. Use lifecycle history filters explicitly for historical questions; do not present superseded material as current.
  5. Distinguish no matches from inaccessible, invalid, incomplete or failed reads. Follow result offsets with unchanged filters and, for keyword search, compare index.snapshot. If an API pagination bound prevents exhausting results, narrow the query or state the coverage limit. Do not claim the vault lacks something solely because a short ranked list did not contain it.

Recall itself is read-only. If the selected Knowledge memory policy calls for remembering genuinely new durable information, use knowledge-capture separately. Do not re-save retrieved summaries as new evidence or enrich entities merely because they appeared in an answer.

Temporal questions

Use knowledge_chronicle_day for a day/week, knowledge_chronicle_since for an occurrence range, knowledge_timeline for an entity's dated records or a chosen timeField, and knowledge_chronicle_last_seen for latest dated context. Resolve an entity to a stable page ID first. Dated mentions do not prove attendance. For keyword/inventory queries add since/until and timeField to knowledge_grep or knowledge_records. occurred_at answers when something happened; recorded_at and updated_at answer when records were created/changed. Never substitute one for the other. Resolve relative query dates with the user's timezone, preserving explicit offsets; day queries accept an IANA timezone. Source date-only values stay date-only. Follow nextOffset with unchanged filters and returned snapshot. Temporal eligibility="include_inactive" includes superseded/expired material, never withdrawn records or a reconstruction of past system state. Last-seen uses occurredOnOrBefore for the occurrence cutoff; do not pass asOf or historical. Use includeSources=true for deduplicated source identities on temporal pages. Markdown-only timelines and undated records are not inferred, and no matches do not prove absence.

Focused source reading

Use knowledge_evidence_read with the record id and observed path/sha256 to read an exact retained UTF-8 passage. Supply inclusive startLine/endLine when known. Follow nextCursor with unchanged id/path/hash and omit or repeat line bounds. A null nextCursor completes the passage. In contrast, record.nextEvidenceOffset only completes the citation list; excerptTruncated still requires source reading. The tool verifies bytes and line bounds, not the truth of an interpretation. Use knowledge_attachment for binary originals. Never infer complete review from an excerpt or a successful structural verifier.

Query freshness distinguishes queriedAt from scannedAt; keyword results also have indexedAt. A reused scan retains its observation time. Compare snapshot values only across pages with unchanged query filters and eligibility.

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