athena_witness_cell

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

With no annotations, the description carries the full burden of behavioral disclosure. It conveys important execution traits: isolated Python mode, sanitized environment, timeout, network-socket monkeypatch, and POSIX resource caps when available. It also includes an honest caveat that it is not OS-hermetic, which sets accurate expectations. However, it does not state what the tool returns or whether side effects might occur beyond the described isolation.

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 a single, information-dense sentence that puts the core action upfront and uses every word to add value. The final caveat 'Not claimed OS-hermetic' is a concise, useful limitation statement. There is no redundancy or filler.

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 is behaviorally rich but incomplete in key areas. It does not explain what a 'witness' is, how to populate the required regression_ref parameter, or what the tool returns. Given there are no annotations and no output schema, the agent must rely on bare parameter names to infer inputs and has no guidance on outputs. This makes the description only partially complete for a tool with five parameters.

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 0%, and the description does not map any of the five parameters to their meanings. The schema provides only names and types, e.g., regression_ref, cpu_s, memory_mb, timeout_s, and actor, but no descriptions. The description generically mentions 'timeout' and 'resource caps' but does not explicitly tie them to specific parameters. This fails to compensate for the schema's lack of detail.

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: executing one repository-owned unittest witness. It specifies the verb 'execute' and the resource 'repository-owned unittest witness', and adds scoping details like isolated Python mode and sanitized environment. However, it does not explicitly distinguish itself from sibling tools such as athena_antibody_execute_regressions, which may also execute tests, 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?

Usage is implied: this tool is for executing a specific unittest witness. However, the description provides no explicit guidance on when to use this versus other tools, nor does it mention any exclusions or prerequisites. It is clear enough to infer a use case but lacks explicit decision support.

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