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Glama

validate_claim

Verify factual, mathematical, or scientific claims before presentation to catch hallucinations. Returns coherence, confidence, and deterministic status for each claim.

Instructions

Intercept and validate a factual, mathematical, or scientific claim before presenting it. Returns Coherence Index (0.0-1.0), Confidence Score (0%-100%), and Deterministic Status (VERIFIED_COMPUTED_PASS, REJECTED_HALLUCINATION, BOUNDARY_BREACH, or NEEDS_REVIEW).

Input Schema

NameRequiredDescriptionDefault
claimYesThe text proposition, calculation, or claim to validate.
contextNoValidation domain or context (default: 'general_domain').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose the return surface: Coherence Index, Confidence Score, and the four Deterministic Status values. It does not state that this is a non-destructive/read-only operation or name any cost, latency, or side effects, which is the remaining gap.

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?

Two tight sentences with the action front-loaded and the return values enumerated after. Every clause carries information, though the status enum list is dense and could be structured more readably.

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?

For a two-parameter tool with no output schema, the description supplies the missing return-value detail, which is exactly its job. An agent has enough to call it and interpret results, though the absence of any safety/behavior profile is a modest gap.

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 parameters are already documented, making 3 the baseline. The description adds no semantics for 'claim' or 'context' beyond what the schema states.

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+resource: 'intercept and validate a factual, mathematical, or scientific claim' with the scoping condition 'before presenting it.' It is distinguishable from siblings like compute or solve_equation, though it never explicitly contrasts itself with verify_step or epistemic_consensus.

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

Usage Guidelines3/5

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

The phrase 'before presenting it' implies the usage moment (pre-output gating), but there is no explicit when-not guidance and no routing to alternatives such as verify_step or epistemic_consensus, which appear to overlap in purpose.

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