Retrieve detailed information about a specific GitHub project, including its structure, tasks, and current status, to support project management and tracking.
Get details of a specific GitHub project
| Name | Required | Description | Default |
|---|---|---|---|
| projectId | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it 'gets details' but doesn't clarify if this is a read-only operation, what permissions are required, whether it's idempotent, or how errors are handled (e.g., invalid project IDs). For a tool with zero annotation coverage, this leaves critical behavioral traits unspecified.
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 a single, front-loaded sentence with zero wasted words—it directly states the tool's function. Every word ('Get details of a specific GitHub project') earns its place by clarifying scope and resource, making it highly efficient and well-structured.
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?
Given the tool's low complexity (1 parameter, no nested objects) but lack of annotations and output schema, the description is incomplete. It doesn't explain what 'details' include in the return value, error conditions, or dependencies on other tools (e.g., 'projectId' from 'list_projects'). For a read operation with no structured output documentation, more context is needed to guide effective use.
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?
The input schema has 1 parameter ('projectId') with 0% description coverage, so the schema provides no semantic context. The description implies the parameter identifies 'a specific GitHub project' but doesn't specify format (e.g., numeric ID, URL) or sourcing (e.g., from 'list_projects'). This adds minimal meaning beyond the schema's structural definition, aligning with the baseline for low coverage.
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 verb ('Get') and resource ('details of a specific GitHub project'), making the purpose unambiguous. It distinguishes from siblings like 'list_projects' (which returns multiple projects) by specifying retrieval of a single project's details. However, it doesn't specify what 'details' include (e.g., fields, metadata), which prevents a perfect score.
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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a project ID), contrast with 'list_projects' for browsing, or specify scenarios like retrieving metadata for editing. Without such context, the agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.