boss_ai_optimize

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

With no annotations, the description still carries useful behavior: the operation is non-destructive because it returns an optimized structure rather than writing to disk. That is the single most valuable disclosure here. It does not say whether the optimization is persisted anywhere, whether it costs credits/is rate-limited, or what the output object contains beyond 'structure'.

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?

One front-loaded sentence plus a compact availability tag; nothing is padded. The availability metadata is dense but readable and communicates real preconditions rather than boilerplate.

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 two-parameter, no-annotation, no-output-schema mutation-like tool, the definition covers intent and the no-write guarantee, which is the critical part. It leaves the return shape vague ('optimized structure') and never explains how to obtain a valid resume identifier, so an agent could stall on inputs.

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 both parameters are documented in the schema and the baseline is 3. The description adds that jd_text is the target job description being optimized against, which gives purpose but no format or length guidance, and it does not clarify where the 'resume' name value comes from (boss_resume_list/boss_resume_show).

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 resource ('optimize resume based on target job description') plus a scoping clarification ('outputs optimized structure, does not write to disk'). However it does not distinguish itself from the near-identical sibling boss_ai_resume_optimize, so an agent still has to guess which of the two to pick.

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 availability bracket gives real gating (roles=candidate, candidate_platforms=zhipin, recruiter_platforms=-), which tells the agent when the tool is usable. It says nothing about when to prefer it over boss_ai_resume_optimize, boss_ai_analyze_jd, or boss_ai_fit, and provides no prerequisites such as needing a resume name from boss_resume_list.

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