estimate_qa_effort

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

With no annotations provided, the description fully bears the burden of disclosing behavior. It states the tool is deterministic, never crashes, returns a structured error on validation failure, and on success returns a comprehensive JSON structure (listing all components). This is complete and clear behavioral disclosure.

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 paragraph that efficiently packs purpose, behavior, and output information. It is reasonably concise, though the dense listing of output fields could be slightly more structured. Overall, every sentence adds value.

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 the tool's complexity (12 params, no output schema), the description covers error handling and output structure but omits parameter details and does not explain the return values beyond listing field names. More context on how to interpret the output (e.g., what each field means) would improve completeness.

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?

The schema has 12 parameters with no descriptions (0% coverage). The description only broadly states that fields mirror the app's project-intake dialogue, but provides no specifics about individual parameters (e.g., format for timeline, allowed values for project_type). This leaves the agent with insufficient guidance for correct input construction.

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 provides a deterministic QA effort estimate using PERT, complexity multipliers, team capacity, and confidence score. It also explicitly contrasts with LLM narrative, making the tool's unique value clear. The sibling tools are all about knowledge retrieval and test analysis, so this estimation tool is well-distinguished.

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 the tool's deterministic nature and that it returns raw numbers for the user to write their own narrative. It also describes validation behavior. However, it doesn't explicitly state when to use this tool over alternatives, though the siblings are not directly competing (they are for knowledge and analysis, not estimation). The context is largely implied.

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