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query_claims

Search claim statements and excerpts, strongest matches first.

Use this when you have keywords or a domain and want the strongest matching claims.
Returns claim id, status, evidence strength, and a shortened excerpt.
Example: query_claims(query="transformer", domain="ai-ml", limit=5).
Example: query_claims(query="United States", domain="data-protection", limit=5).

Input Schema

NameRequiredDescriptionDefault
limitNoPage size. Example: 5.
queryYesText matched against the claim statement and its excerpt. Example: transformer.
domainNoRestrict results to one domain. Example: ai-ml.
offsetNoNumber of hits to skip. Example: 0.
filtersNoOptional status, minimum evidence strength, and assertion type. Example: {"status": "consensus", "min_strength": 0.6}.

Output Schema

NameRequiredDescriptionDefault
pageYes
claimsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed17 schema fields changed
    • addedInput schema / $defs / ClaimFilters / description
      Added value: +"Optional status, strength, and assertion type for a claim search."
    • addedInput schema / $defs / ClaimFilters / properties / assertion_type / description
      Added value: +"Keep one assertion type: asserted, hedged, or conditional. Example: asserted."
    • addedInput schema / $defs / ClaimFilters / properties / assertion_type / examples
      Added value: +[
      +  "asserted"
      +]
    • addedInput schema / $defs / ClaimFilters / properties / min_strength / description
      Added value: +"Drop claims below this evidence strength, from 0 to 1. Example: 0.6."
    • addedInput schema / $defs / ClaimFilters / properties / min_strength / examples
      Added value: +[
      +  0.6
      +]
    • addedInput schema / $defs / ClaimFilters / properties / status / description
      Added value: +"Keep one status: consensus, contested, or outdated. Example: consensus."
    • addedInput schema / $defs / ClaimFilters / properties / status / examples
      Added value: +[
      +  "consensus"
      +]
    • changedInput schema / properties / domain / description
      Previous value: -"Restrict results to one domain."New value: +"Restrict results to one domain. Example: ai-ml."
    • addedInput schema / properties / domain / examples
      Added value: +[
      +  "ai-ml"
      +]
    • addedInput schema / properties / filters / description
      Added value: +"Optional status, minimum evidence strength, and assertion type. Example: {\"status\": \"consensus\", \"min_strength\": 0.6}."
    • addedInput schema / properties / filters / examples
      Added value: +[
      +  {
      +    "min_strength": 0.6,
      +    "status": "consensus"
      +  }
      +]
    • changedInput schema / properties / limit / description
      Previous value: -"Page size."New value: +"Page size. Example: 5."
    • addedInput schema / properties / limit / examples
      Added value: +[
      +  5
      +]
    • changedInput schema / properties / offset / description
      Previous value: -"Number of hits to skip."New value: +"Number of hits to skip. Example: 0."
    • addedInput schema / properties / offset / examples
      Added value: +[
      +  0
      +]
    • changedInput schema / properties / query / description
      Previous value: -"Text matched against the claim statement and its excerpt."New value: +"Text matched against the claim statement and its excerpt. Example: transformer."
    • addedInput schema / properties / query / examples
      Added value: +[
      +  "transformer"
      +]
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations present, the description carries the full disclosure burden; it does cover result ordering ("strongest matches first") and a summary of returned fields, which are useful behavioral traits. It says nothing about permission requirements, result caps, or whether results are stable across pagination, and the read-only nature is only inferred from the word "Search".

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

Conciseness4/5

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

The purpose and ranking behavior are front-loaded in the first line, and the usage sentence follows immediately. The second example call adds little over the first since it only swaps the domain value, making it mildly redundant with the examples already embedded in the schema.

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

Completeness4/5

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

An output schema exists, so the return-value sentence is bonus rather than a necessity, and all five parameters are covered by schema descriptions. What is missing is sibling differentiation against search_smart and any note on pagination interplay between limit and offset, which matters for an offset-paginated search.

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

Parameters3/5

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

Schema description coverage is 100%, so both the top-level and nested filter parameters (status, min_strength, assertion_type) are already fully documented in the schema. The description's examples restate query, domain and limit without adding syntax or filtering semantics beyond what the schema already says.

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

Purpose4/5

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

States a specific verb and resource ("Search claim statements and excerpts") plus a ranking behavior ("strongest matches first"). It does not differentiate itself from the sibling search_smart, so an agent cannot tell from the description alone which search entry point to prefer.

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?

"Use this when you have keywords or a domain and want the strongest matching claims" gives a clear positive trigger, and the two examples reinforce the keyword+domain pattern. There is no when-not guidance and no reference to alternatives like search_smart or get_evidence, which leaves a routing ambiguity.

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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