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boss_ai_reply

Generate reply drafts from recruiter messages, offering 2-3 candidate responses with resume reference and selectable tone for tailored communication.

Instructions

基于招聘者消息生成回复草稿(2-3 条候选,支持简历参考和语气偏好) [可用性: 可用性: roles=candidate; candidate_platforms=zhilian, zhipin; recruiter_platforms=-]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toneNo语气偏好简洁专业
resumeNo参考简历名称(可选)
contextNo会话上下文(可选)
recruiter_messageYes招聘者消息文本
Install Server

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the text carries the full burden, and it does disclose the main behavior: it generates 2-3 draft replies and does not claim to send them. However, it omits details such as how the optional resume/context affect results, any rate limits or service dependency, and it relies on a malformed availability suffix that repeats '可用性'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The main sentence is compact and front-loads the action, result count, and key customization options. The availability bracket is useful but has a duplicated '可用性: 可用性:' and uses terse metadata notation, which slightly lowers polish.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a four-parameter, no-output-schema, no-annotation tool, the description gives the core output shape (2-3 candidate drafts) and role/platform restrictions, which is adequate. It remains incomplete about the exact return structure and how the optional context should be supplied, so it is only minimally viable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 reinforces the role of two parameters (resume and tone) and implicitly ties tone to output style, but it adds little beyond the schema and does not explain the optional 'context' parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb ('生成'/'generate'), a clear object ('回复草稿'/'reply drafts'), and an input condition ('基于招聘者消息'/'based on recruiter message'), so the agent can tell what it produces. The availability suffix clarifies it is for the candidate role on zhilian/zhipin, which indirectly distinguishes it from HR-side reply tools, but it does not explicitly name or compare siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides only implicit usage conditions (candidate role, zhilian/zhipin platforms) and output features. It does not state when the agent should pick boss_ai_reply over nearby alternatives such as boss_ai_chat_coach or boss_hr_reply, and it gives no exclusions or fallback guidance.

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

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