boss_ai_analyze_jd

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

No annotations are supplied, so the description carries the entire behavioral burden and only partially discharges it: it discloses the output shape (score plus gap analysis). It says nothing about cost, latency, quota consumption, whether the call is read-only, or how resume names are resolved, all of which matter for an AI-backed operation with no readOnlyHint.

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 core action and its output are front-loaded in a single compact clause with no filler. The trailing bracketed availability block is dense but earns its space as the only access-control signal present.

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?

With no output schema and no annotations, the description at least names the return contents (match score and gap analysis), which covers the main gap. It stops short of describing result granularity, output language/format, or failure behavior when the named local resume cannot be found.

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%, with both parameters already documented ('职位描述文本' and '对比的本地简历名称'), so baseline 3 applies. The description adds no further meaning beyond the schema — it does not clarify expected length of jd_text or how the resume name is matched against boss_resume_list output.

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?

States a specific compound action: analyze a job description, score resume match, and output gap analysis, which tells an agent exactly what comes back. However, it never distinguishes itself from close siblings such as boss_ai_fit, boss_ai_optimize, or boss_ai_suggest, so an agent must guess which AI-analysis entry point 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 bracketed availability tag (roles=candidate; candidate_platforms=zhipin; recruiter_platforms=-) effectively says who must not use it, which is real exclusion guidance. But it gives no positive conditions — no mention of when to prefer this over boss_ai_fit or boss_ai_optimize — so usage is only implied.

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