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by io.testchimp
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Get Git Folder Mapping

get-git-folder-mapping
Read-onlyIdempotent

Return git provider, repository, mapped plans/tests folder paths, and plans branch (empty = repository default) for the project.

Input Schema

NameRequiredDescriptionDefault
botIdNoQA bots: your botId from your stored TestChimp binding.
projectApiKeyNoQA bots: your own project API key from your stored TestChimp binding. Required on every call except get-bot-credentials, get-project-credentials and get-bot-compat. Never print it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / botId
      Added value: +{
+  "description": "QA bots: your botId from your stored TestChimp binding.",
+  "maxLength": 64,
+  "minLength": 1,
+  "type": "string"
+}
    • addedInput schema / properties / projectApiKey
      Added value: +{
+  "description": "QA bots: your own project API key from your stored TestChimp binding. Required on every call except get-bot-credentials, get-project-credentials and get-bot-compat. Never print it.",
+  "maxLength": 256,
+  "minLength": 8,
+  "type": "string"
+}
  2. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered without the description. The description adds the meaning of the returned branch value ('empty = repository default'), which is genuinely useful context, but says nothing about auth failure modes or what happens when no mapping is configured.

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?

A single dense sentence that front-loads the returned field list with zero filler. Every clause names a distinct output the agent will receive.

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

Completeness4/5

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

With no output schema, the description sensibly enumerates the return fields, which is the main thing an agent needs. It falls short only on edge behavior — what the tool returns or does if no git mapping exists for the project.

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 coverage is 100% and both parameters (botId, projectApiKey) are fully documented in the schema, including the 'Never print it' warning for the API key. The description contributes nothing about parameters, so baseline 3 applies.

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 ('Return') and resource, and enumerates exactly what comes back: git provider, repository, mapped plans/tests folder paths, and plans branch. It is clearly the read counterpart of update-git-folder-mapping, though it never names that sibling explicitly.

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?

There is no when-to-use guidance, no stated prerequisites, and no mention of update-git-folder-mapping as the write alternative. The only guidance-like content is the sentinel explanation for the branch field, which is a value semantic rather than usage direction.

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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