GitHub Actions MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It states the tool fetches logs but doesn't describe what 'logs' include (e.g., console output, timestamps), whether it's a read-only operation, potential rate limits, authentication needs, or the format of the returned data. This leaves significant gaps for an agent to understand how the tool behaves beyond basic functionality.

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, efficient sentence ('Fetch logs for a workflow run') that front-loads the core purpose without unnecessary words. It avoids redundancy and wastes no space, making it easy for an agent to parse quickly. Every word earns its place by directly conveying the tool's function.

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 complexity of a tool with 5 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't address key contextual aspects like what the logs contain, how they are structured, whether the operation is safe (read-only), or any error conditions. For a tool that fetches potentially large data sets, more guidance on behavior and output is needed to help an agent use it effectively.

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 100% description coverage, with all parameters clearly documented (e.g., 'repo' as 'Repository in owner/repo format', 'run_id' as 'Workflow run ID'). The description adds no additional meaning beyond the schema, such as explaining how parameters interact (e.g., 'grep' filters within fetched logs) or providing examples. Since schema coverage is high, the baseline score of 3 is appropriate.

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 'Fetch logs for a workflow run' clearly states the action ('fetch logs') and resource ('workflow run'), making the purpose immediately understandable. It distinguishes from siblings like gha_get_run (which retrieves run metadata) or gha_diagnose_failure (which analyzes failures), but doesn't explicitly mention this differentiation in the description itself.

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 valid run_id), when to use it over gha_diagnose_failure for debugging, or any constraints like authentication requirements or rate limits. The agent must infer usage from the tool name and parameters alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.