detailed_analyze_launch_failures

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

With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: automatic analysis limits (≤10 tests analyzed fully, otherwise first 10), pagination support, screenshot analysis impact on time, Jira smart grouping, and execution mode options affecting speed/safety. It could improve by clarifying output format details or error handling, but covers most critical aspects.

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 front-loaded with the core purpose, but contains some redundancy (e.g., mentioning grouping/statistics/recommendations multiple times) and includes promotional elements like emojis and 'NEW' tags that don't add functional clarity. The tip about auto-invocation is useful but could be more concise. Overall, it's adequately structured but could be tighter.

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 complex tool with 12 parameters and no output schema, the description provides substantial context about behavior, limitations, and practical usage. It covers analysis scope, pagination, format options, and performance considerations. The main gap is the lack of information about return values or output structure, which would be helpful given the absence of an output schema.

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 description coverage is 100%, so the baseline is 3. The description adds some value by explaining the practical implications of parameters (e.g., filterType usage, automatic analysis limits, Jira grouping), but doesn't provide significant additional semantics beyond what's already well-documented in the schema. It reinforces parameter purposes without contradicting them.

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: analyzing failed tests in a launch with grouping, statistics, and recommendations. It specifies the scope (tests without linked issues by default, with filter options) and distinguishes from siblings by mentioning unique capabilities like Jira format with smart grouping and screenshot analysis, which aren't present in other tools like 'analyze_test_failure' or 'get_launch_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?

The description provides clear context on when to use this tool: for analyzing failed tests in a launch, with explicit guidance on filterType options (e.g., 'without_issues' vs 'all'). It mentions auto-invocation from Zebrunner URLs as a tip. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools, though the unique features imply differentiation.

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