popper_learn

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

No annotations are provided, so the description carries the burden. It discloses that outcomes affect the KB on future refutation, but does not mention idempotency, error states, or safety implications like data persistence.

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?

Two sentences: first defines purpose, second defines kinds and critical requirement. No filler or repetition. Ideal conciseness.

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 no output schema and a single parameter, the description covers the core usage. It explains kinds and evidenceAnchors. Lacks info on whether outcomes are appended or replaced, and the return value, but is generally sufficient for an agent to use correctly.

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?

With 100% schema coverage, baseline is 3. The description adds value by explaining the meaning of each kind and emphasizing that held/missed require evidenceAnchors, which the schema lists as optional but the description clarifies as necessary for those cases.

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 verb and resource: 'Record TDD-execution outcomes for the active contract.' It uniquely distinguishes from siblings like popper_hypothesize and popper_refute by focusing on learning from test results.

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 explains when outcomes are folded in ('on the next popper_refute') and notes that held/missed need evidenceAnchors, providing implicit usage context. However, it does not explicitly contrast with sibling tools.

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