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expert_verify_claim

Deterministic check of a (subject, relation, object) claim against an expert's graph — no LLM. Verdicts: supported (a direct edge, matching relation when given), supported_via (a direct edge of another relation, or a 2-hop chain), contradicted (a contradicting edge), unknown (no path within 2 hops; NOT a refutation). Returns the evidence chain with edge evidence text and the source papers. Subject/object accept a node id, an exact name, or search words. [Free · 2 credits]

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "topic_id": "<topic_id>",
      "subject": "<subject>",
      "object": "<object>"
    },
    "name": "expert_verify_claim"
  }
}

Input Schema

NameRequiredDescriptionDefault
objectYes
subjectYes
relationNoEdge type, e.g. uses, evaluated_on, introduces, supports_claim.
topic_idYesTopic id of an expert (from list_experts).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations supplied, the description carries the full behavioral burden and does so strongly: it discloses determinism/no LLM, the exact verdict taxonomy, the two-hop traversal limit, the meaning of 'unknown', the returned evidence chain and source papers, flexible subject/object input, and the cost.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The definition is front-loaded with the core purpose, then compactly covers verdict semantics, return contents, accepted parameter forms, and cost. The verdict list is dense but every clause carries operational value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a four-parameter deterministic verification tool with no output schema, the description covers what the tool does, how verdicts should be interpreted, what evidence is returned, and how inputs can be supplied. Nothing essential for correct invocation appears to be missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 50%, but the description compensates by explaining that subject and object accept a node id, exact name, or search words, and by clarifying the role of relation in verdict matching. It adds little for topic_id beyond the schema's own expert-graph context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource — a deterministic (subject, relation, object) claim check against an expert's graph — and explicitly contrasts it with LLM-based behavior. This makes it distinguishable from siblings such as expert_ask and expert_search_facts without requiring schema inspection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It clearly establishes the deterministic verification use case and explains what each verdict means, including that 'unknown' is not a refutation. It does not explicitly name when to prefer expert_ask or expert_search_facts instead, so it falls short of full alternative routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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