suggest_profile_by_job

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

With no annotations provided, the description carries the full burden and does an excellent job. It discloses the data source (real anonymized employee database, 417 positions), the algorithm (profiles occurring in >=40% of employees), the output details (% coverage and employee count), and the fuzzy search behavior. This gives the agent a solid understanding of what the tool will do.

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 two sentences, front-loaded with the core purpose and then succinctly adding key behavioral details. There is no fluff or repetition; every sentence earns its place.

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?

Despite no output schema, the description adequately explains what the tool returns (profiles with coverage % and employee counts). It also covers the matching logic and the threshold concept. For a suggestion tool of moderate complexity, this is complete enough for an agent to select and invoke 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 description coverage is 100%, so the baseline is 3. The description adds some context about the fuzzy search and data corpus, but these are already partially reflected in the schema's parameter description for job_title ('Поддерживается частичное совпадение'). It does not significantly augment the parameter meaning beyond what the schema provides.

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 a specific verb ('Подбирает' - selects) and a specific resource ('типовые профили доступа 1С' by job title). It further differentiates itself by mentioning the data source (417 job titles), the coverage threshold (>=40%), and fuzzy search, which distinguishes it from sibling tools like search_by_role or suggest_access_profile.

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 implies a clear usage context: when you have an employee's job title and need typical access profiles. It gives practical examples in the schema ('кладовщик', 'бухгалтер') and explains the fuzzy matching behavior. However, it does not explicitly state when not to use this tool or name alternatives like suggest_access_profile, so it misses the top score.

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