get_test_history

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the returned health_status values (healthy/flaky/broken/disabled/insufficient_data) and the test_health view source, but says nothing about read-only safety, result volume, or pagination.

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?

Three short sentences, front-loaded with the purpose before the usage hint and output detail. The health_status enumeration is the only mildly dense element and it earns its place by naming concrete return values.

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 read-only stats tool with no annotations and no output schema, the description covers purpose and one output field but leaves return shape, data volume, and time-window semantics largely unspecified. Adequate but not thorough for the complexity level.

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 all four parameters (days, spec_file, project_id, test_title) are already documented in the schema. The description adds no syntax, format, or default guidance beyond what the schema provides, so the baseline of 3 applies.

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 gives a specific verb (Get) and resource (historical pass/fail/flaky statistics) scoped to a single test, which an agent can distinguish from siblings like get_flaky_specs or get_test_trend. It does not explicitly name a sibling to contrast against, so it falls short of a 5.

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?

'Use this to understand how often a test fails and its overall reliability' implies the use case but never states when to prefer this over get_test_trend, get_flaky_tests, or get_recent_failures. No exclusions or prerequisites are given.

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