get_submission_detail

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

With no annotations provided, the description carries full burden and does well by disclosing key behaviors: it parses template sections, hides GitHub usernames during scoring but retains them for reports, fetches READMEs from GitHub repositories, and raises RuntimeError on command execution failure. However, it doesn't mention rate limits, authentication needs, or pagination behavior.

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 well-structured and front-loaded with the core purpose, followed by behavioral details and parameter/return documentation. Every sentence adds value without redundancy, and the Args/Returns/Raises sections are efficiently organized.

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 single-parameter tool with no annotations and no output schema, the description provides good coverage: purpose, behavioral traits, parameter meaning, and error handling. It could be more complete by detailing the return dictionary structure or authentication requirements, but it's substantially adequate given the context.

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?

With 0% schema description coverage and only one parameter, the description adds significant value by explaining that 'issue_number' is 'The Issue number to fetch', providing context beyond the schema's title. It doesn't specify format constraints or examples, but compensates adequately for the schema gap.

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's purpose with specific verbs ('fetch detailed submission data', 'parses each section', 'returns scoring data') and identifies the resource ('Issue number'). It distinguishes from siblings by focusing on detailed parsing of individual submissions rather than listing, generating reports, or managing rubrics.

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 implies usage context by specifying 'for the specified Issue number' and mentioning scoring data, but doesn't explicitly state when to use this tool versus alternatives like list_submissions or generate_ranking_report. No exclusions or prerequisites are provided.

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