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compatsy 3D printing

Report a data issue

report_issue

Flag a wrong spec, price or fit verdict. Reports never edit facts; two independent reports mark a fact disputed. Example: {"entity_type":"product","entity_id":"prusa-mk4s","field":"nozzle_thread","claim":"MK4S uses the Nextruder thread"}

Input Schema

NameRequiredDescriptionDefault
claimYes
fieldNo
entity_idYes
entity_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations only say it is non-read-only, non-destructive and non-idempotent. The description adds real value beyond them: reports do not edit facts, and two independent reports are what mark a fact disputed — behavior an agent cannot infer from structured fields. It leaves unclear what a single report does on its own (stored? queued? acknowledged?).

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 short sentences and an example, with the core action front-loaded and the dispute-threshold rule second. Every clause adds information; nothing is padding.

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?

There is no output schema, and the description never says what calling it returns or what happens to a single report before a second one arrives. Combined with 0% schema coverage on four parameters, meaningful gaps remain for an agent deciding whether the call succeeded and how to phrase 'field'.

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 0%, so the description must carry parameter meaning, and the embedded JSON example at least maps values for entity_type, entity_id, field and claim. But it never explains what 'field' means (which field names are valid, why it is optional), nor the allowed entity_type values or the 500-character claim limit.

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 and resource: 'Flag a wrong spec, price or fit verdict', which immediately sets it apart from the read-only siblings (check_fit, check_stock, get_product, search_products, compare). The 'Reports never edit facts' clause further pins down that it files a report rather than mutating data.

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 makes clear when to call it (you found a wrong spec, price or fit verdict) and supplies a worked example, which is strong selection guidance. It stops short of naming an alternative path or stating any exclusion (e.g., when to use compare or check_fit instead of reporting).

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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