Skip to main content
Glama

boss_ai_chat_coach

Analyze BOSS Zhipin chat logs to diagnose conversation status, then generate next-step action advice and ready-to-send message templates for candidates.

Instructions

基于聊天记录诊断沟通状态并给出下一步行动建议与现成消息模板 [可用性: 可用性: roles=candidate; candidate_platforms=zhipin; recruiter_platforms=-]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNo沟通风格偏好(如 简洁专业/积极主动/谨慎稳重)简洁专业
resumeNo参考简历名称(可选)
chat_textYes聊天记录文本

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.19.1
  2. Removedv1.18.0
  3. Addedv1.17.0
  4. Removedv1.16.0
  5. First observedv1.11.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the disclosure burden. It implies a non-mutating diagnostic (it 'diagnoses' and 'suggests'), and the availability line adds who-can-call context, but it says nothing about whether state changes, token cost, or how templates are generated. Moderate rather than rich disclosure.

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?

A single front-loaded sentence captures the core action plus outputs, and the availability tag is appended. Slightly marred by the duplicated '可用性: 可用性:' text, but overall tight and well-ordered.

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

Completeness4/5

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

For a no-output-schema tool, the description names the return artifacts (diagnosis, next-step actions, message templates) so an agent knows what to expect. Combined with 100% schema coverage, it is largely complete, though it lacks differentiation from siblings and any note about template/style interaction.

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 chat_text, style, and resume are already documented in the schema. The description adds no parameter-level meaning beyond that, so the baseline 3 for full schema coverage applies.

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?

States a specific verb and resource: diagnose communication status from chat records and return next-step suggestions plus ready-made message templates. Clear about the output artifacts (diagnosis + action advice + templates), but does not differentiate itself from plausible siblings like boss_ai_reply or boss_ai_suggest.

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

Usage Guidelines3/5

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

The availability tag (roles=candidate; candidate_platforms=zhipin; recruiter_platforms=-) implicitly gates when the tool can be invoked, which is useful. However there is no explicit guidance on when to choose this over sibling reply/coach tools, 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.