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

Annotations already declare this a read-only, idempotent, closed-world operation, so the safety profile needs no restatement. The description still adds real behavioral context beyond them: result rows are 'compact', items must be explicitly loaded afterwards, their url should be cited, and the search is plain rather than model-backed. It stops short of describing ordering or pagination interaction between limit and offset.

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 most decision-relevant fact — search one item here, use start_outcome for a business goal — is front-loaded, and the rest is packed into tight parenthetical clauses. It is dense rather than padded, though the parenthetical style makes it slightly harder to scan than plain sentences.

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?

For a 10-parameter discovery tool with a full output schema and rich annotations, the description covers routing, browse-vs-query semantics, and the required follow-up workflow. What remains unstated (paging behavior, category's meaning) is either in the schema or not essential to calling 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 60% on 10 parameters, so the description needs to help and it does: it groups type, job, level, tested and since as filters, and crucially explains the cross-parameter behavior that 'job or since' acts as a browse trigger when query is omitted. limit, offset, category and response_format are left to the schema, which is acceptable given the schema documents most of them.

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 verb and scope ('Find one item for a task'), then enumerates exactly what is searchable (skills, workflows, agents, prompts, minds, AI tools, mini tools). It also draws a boundary against a sibling by name: 'for a whole business goal, use start_outcome', so an agent can distinguish this from outcome-oriented tools 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?

It clearly explains the two operating modes ('With no query, a job or since browses' vs keyword/intent search) and prescribes the follow-up path: load only chosen items with get_skill, get_workflow or get_item. The one gap is that other search-adjacent siblings such as search and find_specialist are never contrasted, leaving a sliver of routing ambiguity.

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