get_test_results_detailed

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

With no annotations provided, description fully carries behavioral disclosure. It reveals the tool fetches from S3, not GraphQL, automatically scans for error patterns, and returns a structured summary with top error terms and example lines. This goes beyond a simple 'get content' description, though it doesn't detail auth mechanics or rate limits.

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?

Description is extremely concise: two sentences covering core functionality, plus a short usage guideline. Every sentence adds value, no redundancy. Front-loaded with primary purpose.

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 moderate complexity (5 parameters, output schema exists), the description covers core functionality, usage context, output characteristics (error scan), and prerequisites. It is self-contained and complete for an agent to understand invocation.

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 100%, but description adds valuable context beyond schema. For test_name, it explains typical values for resmoke tests; for tail_limit, it clarifies default purpose; for task_id, it specifies source. This enriches parameter understanding.

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?

Description clearly states the tool fetches raw test log content from S3, explicitly distinguishing it from GraphQL-based tools. It provides specific verb+resource (Get raw test log content) and hints at its unique value (scanning for error patterns). The purpose is clear and differentiates from sibling tools like get_test_results_summary and get_task_log_summary.

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?

Explicitly states when to use: to understand WHY a test failed. Provides prerequisite: requires task_id and test_name from get_patch_failed_jobs. However, does not explicitly mention when not to use or list alternative tools, though context implies summary tools are for lighter needs.

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