get_test_history

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

The description discloses that the tool reads snapshot files (non-destructive) and returns summary data. While no annotations are provided, the behavioral traits are adequately covered, though it does not mention any potential performance implications or error handling.

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 concise enough, covering the core functionality in a few sentences with key information front-loaded. It could be slightly more compact, but it is not verbose.

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?

The description fully explains the tool's purpose, return fields, use cases, and parameter. Given the simple input schema and no output schema, the description provides sufficient context for correct usage.

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% and the parameter 'limit' is well-documented in the schema with default, range, and use-case recommendation. The description adds minimal additional meaning, so baseline 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 clearly states the tool traverses test history snapshots and returns per-run summaries with specific fields (timestamp, total, passed, etc.). It also lists concrete use cases (flake analysis, speed degradation, coverage trends), making the purpose unambiguous.

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 explicitly states when to use the tool (e.g., flake analysis, speed degradation) and directs users to a sibling (get_optimization_plan) for actionable suggestions, providing clear guidance on tool selection.

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