research.generate_specs

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

With no annotations, the description carries full burden. It discloses the write action and the guard condition (approved=true), but omits details on failure modes, idempotency, side effects, or auth requirements. Adequate but not comprehensive.

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 with front-loaded main action, prerequisites, and details. No filler, 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?

Good overview of purpose and prerequisites, but lacks parameter explanations and return details. Given 5 parameters and no output schema, more context would be needed for complete understanding.

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 40%, and the description adds minimal parameter context. It implies the approved parameter's role but does not explain intent, hypothesis, runId, or research parameters. The description fails to compensate for low schema coverage.

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 it writes research-backed Atomic Design specs from ResearchStore V2, differentiating it from sibling tools like get_spec or create_spec. It explicitly mentions prerequisites and lists the spec types written.

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 provides explicit prerequisites: call research.design_package first and set approved=true. It does not list when not to use or alternatives, but the context suggests this is for batch generation from research.

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