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ecosystem_start_integration

Constructs a task creation payload, adds lifecycle:integrated tag, advances stage status, and returns ready-to-POST task details for integration.

Instructions

Stage 3 integrate path — build a task_create payload + tag the repo.

Adds lifecycle:integrated tag, advances stage_status, and returns a task payload (title / description / priority / horizon / tags) ready to POST to /api/projects/{project_id}/tasks. After the task is created, call ecosystem_link_integration_task to write integration_task_id back onto the review.

ecosystem 不接管实施 — task ownership 由现有任务/团队系统接管。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNoOptional task title (auto-generated if empty).
horizonNoTask horizon — short / mid (default) / long.mid
priorityNoTask priority — critical / high (default) / medium / low.high
extra_tagsNoAdditional tags appended to the task.
descriptionNoOptional task description (auto-generated if empty).
deep_review_idYesTarget deep_review row id (must be debated / architecture_done / referenced).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries full responsibility. It clearly states the tool adds a tag, advances stage_status, and returns a ready-to-post payload. This sufficiently discloses state changes and output without contradiction.

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 compact and well-structured, with a clear purpose first, followed by action steps and a follow-up note. The Chinese line about ownership is slightly extraneous for English-agent contexts but adds important context. No redundancy.

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

Completeness5/5

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

Given the tool's complexity (producing a payload for an external API, requiring a follow-up call), the description covers all necessary steps: what it does, what it returns, and what to do next. It also clarifies that ecosystem does not own the implementation, which is critical for correct multi-step workflow.

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?

With 100% schema description coverage, the baseline is 3. The description adds no additional detail beyond the schema for parameters; it restates the same info (e.g., 'Optional task title (auto-generated if empty)'). Thus, it meets but does not exceed expectations.

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

Purpose5/5

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

The description clearly states the tool's purpose: to build a task_create payload and tag the repo during Stage 3 integration. It explicitly names the sibling follow-up tool, setting it apart. The verb 'build' and specific actions 'adds tag', 'advances stage_status' are unambiguous.

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 description indicates when to use this tool (Stage 3 integrate path) and references the next step (call ecosystem_link_integration_task). However, it does not provide explicit when-not-to-use scenarios or compare to alternatives, relying on context.

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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