gluecron_explain_repo
Return the cached AI 'explain this codebase' Markdown for a repo. Pure read — never triggers a new generation (use the web UI for that).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | ||
| owner | Yes |
Return the cached AI 'explain this codebase' Markdown for a repo. Pure read — never triggers a new generation (use the web UI for that).
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | ||
| owner | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds value beyond annotations by explicitly stating 'Pure read — never triggers a new generation', which aligns with the readOnlyHint and provides specific behavioral context about caching. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences that front-load the purpose and immediately add a critical behavioral constraint. Every word adds value, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only retrieval tool with two standard parameters and no output schema, the description adequately covers core behavior (returns cached Markdown), return format hint (Markdown), and safety profile (read-only). No missing information given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description does not explain the 'owner' and 'repo' parameters beyond what is obvious from their names. With no additional parameter guidance, the description fails to help agents understand input format or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns cached AI Markdown for a repo. It uses specific verb 'Return' and resource 'cached AI explain this codebase Markdown', and distinguishes from tools that trigger new generations by explicitly saying 'never triggers a new generation'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: use this when you want the cached explanation without triggering a new generation. It implicitly contrasts with other tools that generate new explanations, but does not explicitly name sibling alternatives like 'repo_explain_codebase'.
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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