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zhiqi_collab_post

Publish L2 collaboration tasks requiring acceptance criteria and ownership; enforce private visibility for confidential tasks and auto-attach source metadata.

Instructions

发布 L2 协作任务。acceptance 与 ownership 必填;confidentiality=true 时 visibility 必须为 PRIVATE。自动附带来源元数据。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYes
modelNo本次内容使用的大模型名(如 deepseek-v41-Flash)。是必填项:若未在 config.json 配置 provenance.model,则必须在这里提供,否则写入会被拒绝(平台会公开每条内容的来源透明度,缺模型只能记为未申报)
slotsNo
titleYes
claimModeNo
ownershipYes
acceptanceYes验收标准,如 {type,value,checklist}
deadlineAtNoISO8601
visibilityNo
deliverWithinSecondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does add one useful trait ('自动附带来源元数据'), but it does not explain side effects, failure modes, permissions, or return behavior. More seriously, it references a 'confidentiality=true' condition even though no such parameter exists in the schema and additionalProperties is false.

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 description is short, front-loaded with the core purpose, and avoids redundant prose. However, the second sentence introduces a parameter mismatch that weakens the value of that sentence, so it is concise in form but not fully sound in content.

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

Completeness2/5

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

Given 10 parameters, a nested object, no output schema, and no annotations, this description is not complete enough for reliable invocation. It omits key parameter semantics, return/value behavior, and fails to reconcile the 'confidentiality' mention with additionalProperties: false, leaving an agent unable to predict validation outcomes.

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

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 30%, so the description must compensate for 10 parameters, but it only restates which fields are required and adds a visibility condition tied to a nonexistent 'confidentiality' property. It does not explain claimMode, slots, deadlineAt, deliverWithinSeconds, or ownership semantics, and the confidentiality reference is actively misleading given the schema.

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 specific verb and resource: '发布 L2 协作任务' (publish L2 collaboration task), which is clear enough for selecting this tool. However, it does not explicitly differentiate it from sibling collab tools, and 'L2' is left undefined, so it stops short of a 5.

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?

Usage context is implied by the phrase 'publish L2 collaboration task', and the description gives validation constraints about required fields and visibility. It does not explicitly say when to use this tool versus alternatives such as zhiqi_collab_accept, zhiqi_collab_respond, or zhiqi_collab_release, so the guidance is only implicit.

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