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check_policy_only

Validate a draft against configured policy rules alone, flagging prohibited claims and missing AI disclosure before publication.

Instructions

Check a draft against a policy alone - prohibited claims and AI disclosure.

This is the half that needs no evidence and no model: the constitutional layer. It answers "would our own rules let this out of the door", which is a different question from "is it true".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
draftNo
draft_pathNo
policy_jsonNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses that this path requires no evidence and no model (i.e., it is a cheap, self-contained policy check) and enumerates what is checked, but says nothing about failure modes, what happens with a malformed or missing policy, or how strict the verdict is.

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-loaded with the core purpose, then a short elaboration and a framing contrast. The 'constitutional layer' flourish is a bit decorative but brief, and no sentence is redundant.

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 values need not be explained, and the scope of the check is clear. However, with no annotations and zero parameter documentation, an agent still lacks guidance on how to supply the draft and policy, leaving the definition incomplete for a 3-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Three parameters at 0% schema coverage, and the description explains none of them. The ambiguity between 'draft' (inline text?) and 'draft_path' (file path?) is exactly the kind of thing the description should resolve, and 'policy_json' is likewise undocumented. This is a real gap the description fails to compensate for.

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 and resource ('Check a draft against a policy alone') and names the check contents (prohibited claims, AI disclosure). It distinguishes itself from the evidence/model-based siblings by describing itself as 'the half that needs no evidence and no model', though it never names check_draft directly.

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?

Gives a clear selection condition: use this when only the policy layer matters and no evidence or model is needed, contrasted against the 'is it true' question other tools presumably answer. It stops short of explicitly naming the alternative tool to use instead when truth/evidence matters.

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