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by io.testchimp
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Get Branch Specific Endpoint Config

get-branch-specific-endpoint-config
Read-onlyIdempotent

Resolve BASE_URL for a Git branch from TestChimp Branch Management (URL template and per-branch overrides).

Input Schema

NameRequiredDescriptionDefault
botIdNoQA bots: your botId from your stored TestChimp binding.
branchNameNo
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

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the resolution logic (URL template plus per-branch overrides), but says nothing about auth requirements, error behavior, or what happens when no branch override exists.

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 front-loaded sentence with no filler; the key concept (BASE_URL resolution for a branch) leads and every clause earns its place.

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?

With no output schema, the description must carry the return-shape burden; it implies a BASE_URL is returned but does not state the response structure or fallback behavior. Combined with zero required params (all optional), the agent lacks guidance on what happens if inputs are omitted.

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 67%, with botId and projectApiKey documented in-schema. The description only hints at branchName via 'for a Git branch' and adds no syntax or format detail beyond the schema, so it does not compensate for the remaining gap. 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 ('Resolve') and resource ('BASE_URL for a Git branch from TestChimp Branch Management'), which is clear and actionable. It does not, however, name or distinguish itself from the many sibling config/credential tools (get-eaas-config, get-bot-credentials, get-git-folder-mapping).

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

Usage Guidelines3/5

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

Usage is only implied: the agent can infer it should call this when it needs the endpoint base URL for a specific branch. There is no explicit when/when-not, no prerequisite statement, and no routing to alternatives among the large sibling set.

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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