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Gantry

Gantry

by fourn9
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

impact

Read-only

Evaluate how a proposal affects versioned robotics development state by proposal ID, using optional basis and intent context to surface affected artifacts, evidence, and reviews.

Instructions

impact

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "arguments": "<arguments>"
    },
    "name": "impact"
  }
}

Input Schema

NameRequiredDescriptionDefault
argumentsYes
idempotency_keyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.4.0

TDQS

D1.3/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered and the description is not contradictory. However, the description adds nothing beyond that: it does not say what an impact analysis covers, whether it is a computation versus a stored record, or what the caller should expect back.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

There is no wasted wording, but only because there is no wording at all. This is severe under-specification rather than conciseness, and the single token carries no structure an agent could act on.

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

Completeness1/5

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

This is a nested-parameter read operation with no output schema and no parameter documentation, so the description must carry the full explanatory burden and carries none of it. Nothing tells the agent what a proposal impact analysis is, what the basis and intent objects should contain, or how results are returned.

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

Parameters1/5

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

Schema description coverage is 0% and the schema contains nested objects (basis, intent) with no explanation anywhere. The description does not mention proposal_id, basis, intent, or idempotency_key, so an agent must guess at the shape of the two anonymous object parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tautological: description restates name/title.

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

Usage Guidelines1/5

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

There is no when-to-use guidance, no when-not-to-use guidance, and no named alternative. The dense sibling list (why, outcomes, review_context, get_validation_plan) makes routing decisions between them impossible from this definition alone.

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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