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Companion Animation Pipeline MCP Server

Companion Animation Pipeline MCP Server

by arabianguy08

record_review

Records a candidate-bound visual review from an existing evidence JSON file, so you can capture inspection results against a specific animation candidate.

Instructions

Record real candidate-bound visual review from an existing evidence JSON file.

Input Schema

NameRequiredDescriptionDefault
configYes
evidenceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It implies a write/mutation (recording a review) and hints at validation ('real', 'candidate-bound'), but says nothing about side effects, where the review is stored, whether it overwrites prior reviews, required permissions, or what the response contains.

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?

A single tight sentence with no filler, and the action verb and source file are front-loaded. It is efficient, though the brevity borders on under-specification for a tool with two undocumented required parameters.

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

Completeness2/5

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

For a pipeline tool with no annotations, no output schema, and 0% schema coverage, the description is too thin. Missing are the meaning of 'config', the expected evidence file format, what gets persisted, and how this step fits between view_artifact and job_status in the pipeline.

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?

Schema description coverage is 0%, so the description must compensate for both parameters. It clarifies that 'evidence' is an existing JSON file path, but the required 'config' parameter is never mentioned or explained, leaving half the inputs semantically opaque.

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?

The description states a specific verb ('Record') and resource ('candidate-bound visual review') and identifies the source of truth ('an existing evidence JSON file'). The qualifier 'real' hints the review must be genuine rather than fabricated, which is meaningful, though 'candidate-bound' is domain jargon an unfamiliar agent may not decode.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance, no prerequisites, and no mention of how this relates to siblings like pipeline_run, diagnose_stage, or view_artifact. The agent is left to infer that recording a review is a distinct step from running the pipeline or viewing artifacts.

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