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lore_story_decide

Idempotent

Approve or reject a planned StorySpine after review, returning its approval status and spine so you can proceed to drafting or replan with feedback.

Instructions

lore_story_plan이 만든 StorySpine을 승인(active)하거나 거절(rejected)한다. 사용자가 StorySpine 내용을 보고 결정한 뒤 호출한다. 모델 호출 없음. StorySpine이 없으면 오류. 반환은 {approved, spine}. 승인 뒤 다음 단계는 lore_writer_skill.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesapprove=active로 전환한다(생성 때 받은 검증 영수증이 없거나 이후 정본이 바뀌었으면 status=clean_fail). reject=rejected로 표시하고 파일은 지우지 않는다. 거절 뒤에는 lore_story_plan을 feedback과 함께 다시 호출한다.
workIdYes작품 식별자 ([A-Za-z0-9_-]). 한 디렉터리에는 작품 하나만 둔다.
projectNo작품 디렉터리의 절대 경로. 생략하면 서버 실행 디렉터리.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.4.4
    • addedInput schema / properties / action / description
      Added value: +"approve=active로 전환한다(생성 때 받은 검증 영수증이 없거나 이후 정본이 바뀌었으면 status=clean_fail). reject=rejected로 표시하고 파일은 지우지 않는다. 거절 뒤에는 lore_story_plan을 feedback과 함께 다시 호출한다."
    • changedInput schema / properties / workId / description
      Previous value: -"작품 식별자 ([A-Za-z0-9_-])."New value: +"작품 식별자 ([A-Za-z0-9_-]). 한 디렉터리에는 작품 하나만 둔다."
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare idempotentHint=true and destructiveHint=false, so the safety profile is partly covered. The description adds genuinely new context: no model invocation, an error when the StorySpine is absent, the return shape, and the fact that rejection does not delete files (consistent with destructiveHint=false). Missing explicit permission/auth requirements keeps it from a 5.

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

Conciseness5/5

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

Five short front-loaded sentences with zero filler; the core action leads and prerequisites, return, and next step follow in a natural reading order.

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?

For a decision tool with no output schema, the description supplies the return shape ({approved, spine}), the error condition, the reversibility of reject, and the next workflow step — everything an agent needs to call it correctly.

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%, with the enum and both required/optional params fully documented in the schema itself. The description adds no syntax or format detail beyond that, so the baseline 3 is appropriate.

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?

States a specific verb (approve/reject) and resource (StorySpine) and explicitly ties itself to the sibling that produced it (lore_story_plan). An agent can distinguish it from lore_arc_decide / lore_writer_decide without opening any schema.

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

Usage Guidelines5/5

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

It gives the precondition ('call after the user views the StorySpine content and decides'), the failure mode (error if no StorySpine), the reject path (re-call lore_story_plan with feedback), and the follow-on step (lore_writer_skill). When-to-use, when-not, and alternatives are all covered.

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