boss_ai_resume_optimize

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

No annotations are provided, so the description carries the full disclosure burden. It usefully states that the tool only produces suggestions and does not modify the resume, which is an important non-destructive signal for an AI-optimization tool. Beyond that it discloses nothing about return format, permissions, or rate limits.

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 purpose is front-loaded and the whole definition is short. The only blemish is the awkward duplicated label '可用性: 可用性:' in the availability bracket, but the overall length is appropriate.

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 only 3 params, so the description needn't explain return values. It covers the core action and the non-mutating constraint but omits surrounding context such as how optimization output is surfaced or which sibling to prefer, leaving minor gaps for this fairly simple tool.

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 no parameter-level detail (e.g. resume name vs. job_id vs. jd_text semantics) and only addresses tool-level availability, so it does not earn above baseline.

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 ('优化简历措辞' = optimize resume wording) plus scope ('基于目标岗位' = based on the target job). It clearly demarcates the action as advisory ('仅建议，不修改简历'). However, it does not distinguish itself from nearby siblings such as boss_ai_optimize, boss_ai_suggest, or boss_ai_fit, leaving the agent to infer the difference.

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 parenthetical '仅建议，不修改简历' implies an advisory use case, and the availability string (roles=candidate; candidate_platforms=zhipin) tells the agent who/where it applies. But there is no explicit when-to-use vs. when-not, nor any pointer to an alternative sibling tool.

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