Systemonomic

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

With no annotations provided, the description carries the full burden. It discloses the tool's behavior: it assesses tasks across gates, scores them 0-100, and returns classifications with reasoning. However, it lacks details on execution time, error handling, rate limits, or authentication needs, which are important for a batch processing tool.

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 well-structured and front-loaded: first sentence states the purpose, second explains the assessment process, then Args and Returns sections clearly organize parameter and output details. Every sentence adds value with no redundancy.

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 annotations, 3 parameters with 0% schema coverage, and an output schema present, the description is mostly complete. It covers purpose, parameters, and return value overview, but could improve by mentioning execution characteristics (e.g., batch size, timeouts) or linking to sibling tools for better context.

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%, so the description must compensate. It adds meaningful semantics: 'project_id' identifies the project to assess, 'provider' specifies the LLM provider with options and default, and 'model' is optional with provider default. This clarifies beyond the bare schema, though it could detail model compatibility or provider-specific behaviors.

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 specific action ('Run ATSS'), the resource ('all tasks in a project'), and the outcome ('assessed across multiple gates...scored 0-100 for automation suitability'). It distinguishes from siblings like 'get_atss_results' or 'list_atss_runs' by specifying it performs the assessment rather than retrieving or listing 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 implies usage context by specifying it runs ATSS on all tasks in a project, but does not explicitly state when to use this versus alternatives like 'get_atss_results' for retrieving results or 'persist_atss_results' for saving them. It provides clear input requirements but lacks explicit when-not-to-use guidance.

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