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

With no annotations, the description carries the full burden and does well: it discloses that code is mutated, mutant types, that tests are run against each mutant, and that the result includes score and every survivor. It also notes auth context ('Free, no key'), though it omits execution isolation, timeouts, or mutant volume 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?

The purpose is front-loaded, and every clause adds useful information: mutant mechanics, test execution, output contents, and auth context. There is no filler or redundant restatement.

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 two-parameter tool with no output schema and no annotations, the description covers the core contract well: what to submit, what happens internally, and what is returned. It could be more complete by mentioning execution limits, timeouts, or how failing tests are treated, but nothing essential is missing.

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%, so the two parameters are already documented in the schema, including the important detail that tests import 'solution'. The description restates the inputs at a high level but adds no meaningful syntax or format guidance beyond the schema.

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?

States a specific verb and resource ('Mutation-test Python code') and explains exactly what the tool produces: mutation score and survivors. It is clear enough to separate from a health-check sibling in practice, but it never explicitly distinguishes itself from testlens_health.

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?

Usage is implied by the described output ('mutation score plus every SURVIVOR'), but there is no explicit when-to-use vs when-not guidance or named alternative. An agent must infer that this is appropriate when evaluating test suite strength rather than general code quality.

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