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agent_output_verification

Audit an agent's evidence-backed output before forwarding: compare claims to evidence, identify grounded/unsafe claims and orphaned references, and get a per-claim relay verdict.

Instructions

Decide whether another agent's claim-backed output is safe to relay onward. Use before forwarding, publishing, or acting on a downstream agent's answer that cites evidence: it reports which claims are grounded, which are unsafe to relay, and which evidence references are orphaned. Pass audit_json matching evidence-audit.schema.json (claims, evidence records, optional unsupported_claims). Returns a relay verdict with per-claim findings and owner actions. Evidence-readiness only: it does not verify factual truth, fetch or validate cited sources, or authorize an action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audit_jsonYesClaim-level evidence audit of the output being relayed. Call get_schema('evidence_audit') for the full nested contract.
Behavior5/5

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

With no annotations provided, the description carries the full burden of the behavior, and it is unusually transparent: it says the tool reports per-claim findings, returns a relay verdict, and explicitly states it is evidence-readiness only and does not do factual validation, source fetching, or action authorization.

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 definition is compact but information-dense: purpose, use-before conditions, input guidelines, output description, and limitations each earn their place. The most decision-relevant constraint is front-loaded in the first sentence.

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 one required nested object and no output schema, the description is complete enough. It covers what to pass, how it behaves, what will be returned, and what is explicitly not done, giving an agent a realistically safe basis to invoke and interpret the tool.

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 schema already documents the single audit_json parameter fully, so the baseline is 3. The description adds helpful operational meaning by requiring JSON matching evidence-audit.schema.json, listing claims, evidence records, and optional unsupported_claims, so the agent knows exactly what contract to satisfy and where to find more detail.

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 verb and resource: deciding whether another agent's claim-backed output is safe to relay. It goes further by naming the value it produces: which claims are grounded, which are unsafe to relay, and which evidence references are orphaned, positioning it clearly against related verification tools.

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?

The description explicitly lists when to use it: before forwarding, publishing, or acting on downstream claim-backed output. It gives clear exclusions by noting it does not verify factual truth, fetch sources, or authorize action; however, it does not name a specific sibling tool as the alternative for those cases, so the guidance is strong but not fully routed.

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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