P

prove-claim

by @obrav
4.0(120)

利用知识图谱来证明、反驳或调查关于实体及其关系的断言。它有助于探索联系、追溯影响,并对链接信息进行推理,以找到支持或反驳的证据。

knowledge-graphevidenceanalysisreasoninginformation-retrievalGitHub
安装方式
npx skills add https://github.com/obra/knowledge-graph --skill prove-claim
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Before / After 效果对比

1 组
使用前

手动在大量笔记中查找复杂断言的证据,耗时且容易遗漏关键联系,导致结论不完整或不可靠。

使用后

利用知识图谱工具系统地识别所有相关路径和支持/反驳证据,显著缩短时间并提高证据的全面性和可靠性。

SKILL.md

Prove or Disprove a Claim

You have access to a knowledge graph built from an Obsidian vault. The graph contains People, Concepts, Ideas, and conversation summaries connected by wiki links. Your job is to use the graph tools to find evidence that supports or contradicts a claim.

Available Tools

All tools are prefixed with kg_ and accessed via MCP:

ToolPurpose
kg_searchSemantic or full-text search. Start here to find relevant nodes.
kg_nodeGet a node's full content, frontmatter, and connections.
kg_neighborsGet connected nodes at N-hop depth.
kg_pathsFind all connecting paths between two nodes (up to depth 3).
kg_commonFind shared connections between two nodes.
kg_subgraphExtract a local neighborhood as a self-contained graph.
kg_communitiesList detected communities with summaries.
kg_communityGet a specific community's members and structure.
kg_bridgesFind connector nodes (high betweenness centrality).
kg_centralFind important nodes by PageRank.
kg_indexRe-index the vault (run if data seems stale).

The Prove Workflow

Step 1: Decompose the claim

Break the claim into entities and relationships. Identify what you need to find.

Example claim: "Alice's research influenced the Widget Theory concept"

  • Entities: Alice, Widget Theory
  • Relationship: research influence on the concept

Step 2: Find the entities

Use kg_search to locate relevant nodes. Use kg_node to read their content.

  • Search semantically first — it finds conceptually related content
  • Fall back to kg_search with fulltext: true for exact terms
  • Names are fuzzy-matched: "Alice" will find "Alice Smith"

Step 3: Find connections

Use kg_paths to find connecting paths between entities. Read the edge context along each path — it explains why each link exists.

  • Paths go through intermediate nodes (people, concepts, conversation summaries)
  • Use kg_common to quickly find shared connections between two nodes
  • Use kg_neighbors to explore a node's local neighborhood

Step 4: Read the evidence

For each path found, use kg_node on the intermediate nodes to read the actual content. The prose around each wiki link provides context for why the connection exists.

Do not stop at "a path exists." Read the content to verify the connection is semantically relevant to the claim, not just a coincidence of co-occurrence.

Step 5: Assess and report

Report your findings with:

  • Verdict: Supported / Contradicted / Insufficient evidence / Partially supported
  • Evidence chains: The specific paths with quotes from the content
  • Confidence: How strong is the evidence?
  • Caveats: What's missing? What assumptions are you making?

Tips

  • Granola summaries (conversation notes) are the temporal spine — they record when and how concepts were discussed with whom. They're often the richest evidence.
  • Stub nodes (links to pages that don't exist) still carry signal — someone thought the connection was worth noting.
  • Communities group densely-connected nodes. Use kg_communities for holistic questions ("what are the major themes?").
  • Bridges (kg_bridges) are the connector nodes between clusters — often the most interesting nodes in the graph.
  • Multiple short paths between two nodes are stronger evidence than a single long path.
  • Absence of paths is also evidence — if two well-connected nodes have no connection, that's informative.

Provenance and Attribution

When a question involves who originated, created, or owns something, you MUST check attribution before presenting results.

Idea nodes have frontmatter and content that records provenance:

  • Originated by: Alice / Originated by: Bob — in the Status section
  • source: field in frontmatter — where the idea came from (e.g., whatsapp/Some Person)
  • first_mentioned: — when it first appeared
  • Conversation History sections name who proposed what

Before attributing an idea to someone, read the node content and check:

  1. The "Originated by" line in the Status section
  2. The source frontmatter field
  3. The conversation history for who proposed it

If the question is "my ideas" or "what did person X come up with," filter by attribution. An idea that appears in the vault is not necessarily the vault owner's idea — it may have been proposed by a collaborator and recorded here. Getting attribution wrong undermines trust in everything else you report.

When presenting results that involve attribution, explicitly state the provenance: "This was originated by X" or "This came from Y in a conversation on Z date."

Anti-patterns

  • Do NOT claim a connection exists just because two nodes are in the same community.
  • Do NOT treat all paths as equal — a path through a relevant Granola summary is stronger than a path through a generic hub node.
  • Do NOT skip reading the actual content along a path. The graph structure shows that a connection exists; the content shows what the connection means.
  • Do NOT give up after one search. Try synonyms, aliases, related terms. The vault may use different terminology than the claim.
  • Do NOT attribute an idea to someone without checking the provenance fields. An idea recorded in a person's vault may have originated from someone else.

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安装量1
评分4.0 / 5.0
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更新日期2026年5月31日
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创建2026年5月4日
最后更新2026年5月31日
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