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chimera_verify

Verify claims against evidence using lexical token-overlap scoring, returning verdicts of support, contradiction, or insufficiency. Supports NLI and LLM verification methods.

Instructions

Verify claims against evidence using lexical token-overlap scoring. Returns lexically_supported / lexically_contradicted / lexically_insufficient verdicts — IMPORTANT: verdicts are Jaccard token-overlap, not semantic entailment or NLI. Supplement with chimera_constrain for semantic checks. Vs. direct reasoning: provides explicit per-claim scores, curated verification_gold corpus matching, and prompt-injection attack-pattern detection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimsNoClaims to verify. If omitted, extracted from text or envelope.
textNoOptional raw text used to derive claims.
envelopeNoOptional envelope containing value or claims to verify.
evidenceYesEvidence snippets or objects with text/content fields.
corpusNoOptional document pool for grounded verify (RAG). When supplied, the top retrieve_k snippets most relevant to each claim are retrieved (deterministic token-overlap) and used as evidence — you don't have to hand-pick the exact evidence. Merged with any explicit 'evidence'.
retrieve_kNoNumber of corpus snippets to retrieve per claim (grounded verify).
methodNoVerification method. 'lexical' (default): Jaccard token-overlap, fast/deterministic, no extra deps. 'nli': local cross-encoder NLI model (needs [semantic] extra). 'llm': Anthropic judge (needs [llm] extra + ANTHROPIC_API_KEY, non-deterministic).lexical
namespaceNodefault
Behavior5/5

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

No annotations provided, so description carries full burden. It explains verdict types (lexically_supported/contradicted/insufficient), method details (Jaccard token-overlap, deterministic), optional RAG behavior, and method options including dependencies and non-determinism for 'llm'.

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?

Description is well-structured with front-loaded purpose and important caveat. Some repetition (e.g., 'lexical token-overlap' mentioned twice) but generally efficient. Slightly longer than minimal but justified by detail.

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?

Given 8 parameters, high schema coverage, and no output schema, description fully covers tool behavior: verification methodology, RAG, multiple methods, and important constraints. Completeness is excellent.

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 88% (high), baseline 3. Description adds context beyond schema: explains how 'corpus' enables RAG, 'retrieve_k' behavior, and 'method' options with their characteristics. This adds meaningful guidance.

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?

Description clearly states verb 'verify', resource 'claims against evidence', and method 'lexical token-overlap scoring'. Distinguishes from sibling 'chimera_constrain' and contrasts with 'direct reasoning'.

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

Usage Guidelines5/5

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

Explicitly says when to use (verify claims), warns about limitation ('not semantic entailment or NLI'), suggests alternative ('Supplement with chimera_constrain for semantic checks'), and contrasts with direct reasoning.

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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