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Living Stack: check_claim

livingstack.check_claim

Verify a proposed claim against chosen, current, subject-specific evidence to confirm accuracy and support sound decisions.

Instructions

Check a proposed claim against explicitly selected, fresh, successful, subject-bound evidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subjectYesExact claim subject.
claim_textYesExact proposed claim.
session_idYesSession identifier.
outcome_idsYes
max_age_secondsNoEvidence freshness ceiling.
required_evidence_typesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A3.9/5.0
Behavior3/5

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

The description adds meaningful behavioral context by constraining evidence to explicitly selected, fresh, successful, and subject-bound items. However, with all annotation hints false, it does not clarify whether the check itself mutates state, requires authorization, or has side effects, leaving some behavioral ambiguity.

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

Conciseness5/5

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

The entire description is one front-loaded, 12-word sentence with no filler or redundancy. Every phrase carries semantic weight and maps to tool behavior.

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

Completeness3/5

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

An output schema exists, so return-value documentation is not required, but the description omits practical context such as prerequisites (e.g., an active session or previously recorded outcomes) and does not explain how the evidence set is assembled. It is adequate but lean for a tool with six parameters and sibling lifecycle tools.

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?

The description compresses key parameter semantics: 'explicitly selected' maps to outcome_ids, 'fresh' to max_age_seconds, and 'subject-bound' to subject. Schema coverage is only 67%, so this added mapping is valuable, though required_evidence_types remains under-explained.

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?

The description states a specific action ('Check a proposed claim') and a specific resource/evidence set ('explicitly selected, fresh, successful, subject-bound evidence'). This clearly separates it from the lifecycle/status/recording siblings, so an agent can identify when this tool is relevant.

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?

Usage context is implied rather than stated: the agent should call this when it has a proposed claim and selected evidence to verify it against. There is no explicit when-to-use or when-not-to-use guidance, nor any mention of sibling alternatives such as record_outcome, so it falls short of explicit 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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