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fernandogarzaaa

chimeralang-mcp

by fernandogarzaaa
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Python
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chimera_verify

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.

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

NameRequiredDescriptionDefault
textNoOptional raw text used to derive claims.
claimsNoClaims to verify. If omitted, extracted from text or envelope.
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'.
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
envelopeNoOptional envelope containing value or claims to verify.
evidenceNoEvidence snippets or objects with text/content fields.
namespaceNodefault
retrieve_kNoNumber of corpus snippets to retrieve per claim (grounded verify).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.8.4
    • changedInput schema / required
      Previous value: -[
-  "evidence"
-]New value: +[]
  2. First observedv0.8.1

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it flags the critical caveat that verdicts are Jaccard overlap rather than semantic entailment, notes the llm method is non-deterministic, and states what the tool returns per claim. It omits auth/dependency details for the non-default methods (only implied by the schema's 'needs [semantic] extra').

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?

Dense but front-loaded, leading with the action and the verdict caveat before the alternative routing. Every clause carries weight (method caveat, verdict names, sibling pointer), with only mild redundancy against 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?

No output schema exists, and the description compensates by naming the three verdict values an agent should expect. Combined with the method and caveat disclosures, an agent has enough to call it correctly, though the absence of annotations leaves dependency/auth behavior only partially covered.

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 88%, so the schema already documents the parameters and a baseline of 3 applies. The description confirms the grounded-verify behavior of corpus/retrieve_k, but that is largely restated from the schema rather than adding new meaning.

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?

States a specific verb+resource ('Verify claims against evidence') plus the exact method ('lexical token-overlap scoring') and enumerates the three return verdicts. It further distinguishes itself from chimera_constrain (semantic checks) and from direct reasoning, so an agent can place it precisely among siblings.

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?

Explicitly routes the agent: use this for lexical verification and 'Supplement with chimera_constrain for semantic checks.' It also frames the 'Vs. direct reasoning' trade-off. However it gives no explicit when-not-to-use for the many other verify-adjacent siblings (chimera_prove, chimera_confident, chimera_claims), so it stops short of full routing.

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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