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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. Beyond that, the description adds genuine context: the return value is a recommended design with rationale, and it is produced by a real algorithm engine rather than an LLM, which tells the agent the output is reproducible and citable. It does not cover input edge cases, such as what happens with a vague PICO.

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 compact and front-loads the user situation before stating the return value. The trailing parenthetical about the algorithm engine, while useful, reads as a bolted-on credibility claim rather than integrated information.

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?

With no output schema, the description correctly carries the burden of saying what comes back (design plus rationale), which an agent needs in order to route results onward. The remaining gap is guidance on handling vague or underspecified PICO input, which matters given 'pico' is free text and the only required parameter.

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 100%: both 'pico' and 'feasibility' are documented in the schema with clear meaning. The description does not add meaning about either one, notably not explaining how the optional feasibility constraints (case volume, timeline, budget) influence the recommendation. Baseline 3 is appropriate when the schema does the work.

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 states a specific function: it recommends a research design plus the reasoning behind it, for a user who doesn't know which design their question requires. That distinguishes it from siblings that execute a chosen design (act_randomize, act_design_sample_size) or refine the question itself (act_pico_refine), though it never names those siblings explicitly.

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?

It gives an implied trigger condition: use this when the user doesn't know which design they need, or needs to choose an option. It offers no explicit exclusions or hand-offs, so an agent cannot tell from the description when to prefer act_pico_refine or act_design_context first, or what to do after a design is recommended.

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