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Check public claims for stale or missing evidence

check_claims_registry

Audit a product claims registry by flagging each claim as current, stale, or unverified based on evidence presence and freshness, so marketing copy stays aligned after refactors.

Instructions

Keeps public-facing product claims honest over time by checking each one against its own claimed evidence -- the SOC2-control-evidence pattern applied to marketing/product copy instead of compliance controls. Buckets every claim into 'current' (evidence present, review within policy), 'stale' (evidence present but verifiedAt is older than maxAgeDays, or unparseable), or 'unverified' (no evidenceRef at all -- this always wins over staleness, since a fresh date next to an empty reference proves nothing). Use this as a periodic 'Monday-morning' review or a CI gate on a claims registry, to catch marketing copy that drifted out of sync with what the product actually does after a refactor. Note: this only checks that a reference EXISTS and is fresh, not that the thing it points to still actually supports the claim's text -- pair with check_grounding for that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nowNoISO 'now' timestamp to evaluate against. Defaults to the current time.
claimsYesThe claims to evaluate.
maxAgeDaysYesStaleness policy: evidence older than this many days is flagged stale. 0 is valid (every claim must have been verified today or it's stale) -- the kit requires a finite number >= 0.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are supplied, so the description carries the full burden and does so well: it defines the three buckets, the precedence rule ('unverified always wins over staleness'), and the scope limit (existence + freshness only, not grounding). It stops short of stating side effects or that it is a pure read, but the semantic disclosure is strong.

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?

Front-loads the core action, then usage, then the caveat, and every section is relevant. The SOC2-controls analogy costs a few words but meaningfully conveys the pattern, so the size is justified for the tool's complexity.

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 tool with no output schema and no annotations, the description supplies the missing return semantics by naming the three classification outcomes and their tie-breaking. Nothing essential for correct invocation or interpretation appears to be absent.

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 coverage is 100% and every parameter is already documented in the schema (including the empty/whitespace evidenceRef rule and the maxAgeDays semantics). The description reinforces the maxAgeDays/verifiedAt relationship in prose but adds no format or syntax detail beyond the schema, so the baseline of 3 applies.

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 (checking) applied to a specific resource (public-facing product claims registry) and immediately defines the three output buckets. It is clearly distinguishable from siblings, naming check_grounding as the adjacent tool.

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 frames when to use it ('periodic Monday-morning review or a CI gate') and states the boundary condition and the alternative tool to pair with ('not that the thing it points to still actually supports the claim's text -- pair with check_grounding'). This is exactly the when/when-not/alternative guidance expected.

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