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

Annotations already declare readOnly, idempotent, closed-world behavior, so the description only needs to add corpus context — which it does by stating the fixed 173-study corpus, the fields matched, and the full set of returned fields. Minor gaps: no mention of what happens when nothing matches or how ranking works.

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, front-loaded with the action and scope, then matching behavior, then return contents, then filters. The nested parenthetical ('173 studies … each with a strength grade and … summary') is dense but carries relevant corpus context rather than 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?

There is no output schema, and the description compensates by enumerating the returned fields (label, year, journal, design, grade, Loop parts, one-line summary, unfreeze.us page). Combined with the stated matching fields and filter options, an agent has everything needed to call it correctly.

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 coverage is 100%, so the baseline is 3; the description earns above that by explaining that query matches title, summary, setting, authors and journal — a semantic the schema's 'keywords or a short question' wording does not convey. It does not restate part/grade/limit details that the schema already covers.

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?

States a specific verb and resource ('Search the Atlas of the Middle') and pins the corpus scope (173 studies on middle managers and change) plus what is matched. An agent can immediately distinguish this from get_study (single record) and list_loop_parts (taxonomy) without opening any schema.

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?

'Matches words in the title, summary, setting, authors and journal' and 'Filter by Loop part or grade' tell the agent how to use it effectively, and the query field example hints at keyword vs. question style. It never names get_study or get_answer as an alternative, so there is no explicit when-not guidance.

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