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

With no annotations, the description carries the full burden. It discloses that the tool is 'lightweight' and returns 'only NCT IDs and minimal metadata,' which is meaningful behavioral information. It also includes the default max_studies. However, it does not clarify what 'minimal metadata' includes, whether searches across parameter types are AND/OR, or any rate limits or pagination behavior, leaving gaps in transparency.

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 opens with two sentences that are almost redundant: 'Lightweight search returning only NCT IDs and minimal metadata for discovery.' and 'This tool performs a lightweight search that returns only the NCT IDs and minimal metadata for the purpose of discovering relevant trials.' This repetition wastes a sentence. The parameter list is clear, but the redundancy reduces the conciseness.

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, so the description should clarify the response structure. It says 'minimal metadata' but does not enumerate the fields. Additionally, it does not explain how multiple search filters (conditions, interventions, sponsors, terms) interact, which is critical for a search tool. Given these omissions and vague output description, the tool is not fully contextualized.

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%, so the schema already documents all five parameters. The description lists the same parameter descriptions without adding new meaning (e.g., it repeats 'A list of medical conditions to search for'). The only slight addition is mentioning 'Defaults to 100' for max_studies, which is also in the schema. Since the schema carries the semantics, a baseline score of 3 is appropriate.

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 performs a 'lightweight search returning only NCT IDs and minimal metadata for discovery.' This is a specific verb+resource+scope. It does not explicitly distinguish from sibling tools like search_trials_combined, but the name 'nct_ids_only' and the repeated emphasis on 'lightweight' imply a focused search tool. A slightly higher score would require explicit naming of alternatives.

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 notes the tool is 'for the purpose of discovering relevant trials,' implying it is best for early exploration rather than deep detail. However, it does not explicitly state when to avoid this tool or mention alternative tools for full trial data (e.g., search_trials_by_nct_ids or search_trials_combined). This is an implied usage context, not a clear exclusion.

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