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Update Plan Items Lifecycle Status

update-plan-items-lifecycle-status
Idempotent

Update lifecycle_fields.status for one user story or test scenario (DB only; does not rewrite plan markdown). entityType: story | scenario; ordinalId: numeric US-/TS- ordinal; status: draft | ready | in progress | blocked | done | archived. Used after /testchimp implement to set status to ready (unless policy overrides).

Input Schema

NameRequiredDescriptionDefault
botIdNoQA bots: your botId from your stored TestChimp binding.
statusYes
ordinalIdYes
entityTypeYes
projectApiKeyNoQA bots: your own project API key from your stored TestChimp binding. Required on every call except get-bot-credentials, get-project-credentials and get-bot-compat. Never print it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / botId
      Added value: +{
      +  "description": "QA bots: your botId from your stored TestChimp binding.",
      +  "maxLength": 64,
      +  "minLength": 1,
      +  "type": "string"
      +}
    • addedInput schema / properties / projectApiKey
      Added value: +{
      +  "description": "QA bots: your own project API key from your stored TestChimp binding. Required on every call except get-bot-credentials, get-project-credentials and get-bot-compat. Never print it.",
      +  "maxLength": 256,
      +  "minLength": 8,
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare idempotentHint=true, destructiveHint=false, readOnlyHint=false, and the description is consistent with them. It adds real context beyond the annotations by clarifying the write touches the DB only and deliberately leaves plan markdown untouched, though it says nothing about auth/permission requirements or failure modes.

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?

Front-loaded with the core action and scope, then the enum/param details, then the workflow trigger. The semicolon-chained enumeration is dense but every clause carries information; no filler sentences.

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 mutation tool with no output schema, the description covers scope, the DB-only side effect, all required parameter domains, and the intended workflow trigger, with annotations covering the safety profile. Only permission/authorization expectations and any limits on bulk updates are left implicit.

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

Parameters4/5

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

Schema description coverage is only 40%, yet the description compensates well: it enumerates the status enum (draft | ready | in progress | blocked | done | archived), the entityType values (story | scenario), and the meaning of ordinalId (numeric US-/TS- ordinal). botId and projectApiKey are covered by their schema descriptions, so the gap is largely closed.

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 (update) and resource (lifecycle_fields.status) plus the exact scope (one user story or test scenario), and crucially distinguishes itself from update-user-story/update-test-scenario by noting 'DB only; does not rewrite plan markdown'. An agent can pick this over those siblings without opening a schema.

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

Usage Guidelines4/5

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

Gives a concrete usage context: run after /testchimp implement to set status to ready, with the caveat 'unless policy overrides' pointing at the policy tool. It stops short of an explicit when-not or a named alternative for the markdown-rewriting path, so it is clear but not exhaustive.

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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