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Glama

suggest_rewrite

Turn audit findings into rewrite guidance: get offending fragments, policy violation reasons, and suggested replacements grouped by field to patch listing copy.

Instructions

Turn audit findings into concrete rewrite guidance. For each finding it returns the offending fragment, why it violates platform policy, and the suggested replacement — grouped by field so the caller can patch the listing copy directly. Deterministic suggestions only (from the rule pack); this tool never invents copy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNoProduct title
bulletsNoBullet points
keywordsNoSearch keywords
platformYesTarget platform rule pack
descriptionNoProduct description
aiDisclosureNoAI content disclosure status (Amazon 2026-08 rule). One of: "human" (fully human written), "assisted" (partially AI assisted), "ai_generated" (fully AI generated), or empty/null when not yet declared. Declare it honestly: claiming "human" while the copy shows dense AI traces is a RED finding.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
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 meaningful behavior: output is grouped by field for direct patching, and suggestions are deterministic from the rule pack with the strong guarantee that it "never invents copy." It does not cover permissions, rate limits, or what happens when optional fields are omitted, so it is not exhaustive.

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?

Three tight sentences, front-loaded with the core purpose, then the return shape, then the determinism guarantee. Every sentence adds distinct information with no repetition of the title or schema.

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?

There is no output schema, so the description must describe returns, and it does (fragment, violation reason, replacement, field grouping). Combined with the determinism guarantee and full schema coverage on inputs, an agent has everything needed to call and interpret this tool.

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% and the aiDisclosure enum semantics, required platform, and optional copy fields are all fully documented in the schema. The description's only added detail is that results are "grouped by field," which describes output shape rather than input semantics, so it stays at the baseline for a fully documented schema.

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?

Specific verb+resource (turn audit findings into rewrite guidance) with the output contract spelled out: offending fragment, policy rationale, and suggested replacement grouped by field. It implicitly distinguishes itself from audit_listing (which produces the findings) and the rule-pack siblings (which supply rules), so an agent can place it in the workflow without opening any schema.

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 phrase "Turn audit findings into concrete rewrite guidance" clearly establishes the upstream dependency (it consumes audit output) and the intent to patch listing copy. However, it names no exclusion conditions and does not explicitly say when to prefer it over re-running audit_listing or browsing rules.

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