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Team Onboarding Status

team_onboarding_status
Read-onlyIdempotent

View your account's team onboarding status and get the recommended next step.

Instructions

Use when: Human-account tool: show the current account’s team onboarding status and recommended next step. It does not accept actorId. Do not use when: a narrower tool better matches the intent, the project scope is unresolved, or the user has declined the action. Requires: authenticated API authority. Effect: read. Human approval: not required for this read or staging action. Then: follow typed result state; review pending proposals/drafts before any canonical apply. On failure: login_required → login; project_not_selected → list_projects/select_project; permission_denied → stop; stale_version or conflict → read current state; projection_pending → report canonical success separately and wait.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
statusYes
warningsYes
authorityYes
projectIdYes
reviewUrlYes
idempotencyYes
nextActionsYes
reviewRequiredYes
canonicalVersionYes
projectionStatusYes
Behavior5/5

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds significant behavioral context beyond annotations: specifies it does not accept actorId, requires authenticated API authority, effect is read, human approval not required, and details error handling (login_required, project_not_selected, permission_denied, stale_version, projection_pending) and subsequent steps. No contradiction with annotations.

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 structured with labeled sections ('Use when', 'Do not use when', etc.) and front-loads key information. However, it is somewhat verbose with details like 'review pending proposals/drafts before any canonical apply' which could be more concise.

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 no parameters, an output schema, and rich annotations, the description covers usage context, authentication, effect, error handling, and post-action steps. It provides complete guidance for the AI to understand and invoke the tool correctly.

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?

The input schema has no parameters, and schema coverage is 100%. The description adds that it does not accept actorId, which is not a parameter in the schema, clarifying what the tool does not take. This extra context justifies a score above baseline 3 for 0-param tools.

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 clearly states the tool's verb 'show' and resource 'team onboarding status and recommended next step'. It also specifies 'human-account tool' and that it does not accept actorId. However, it does not explicitly distinguish from sibling tools, though no sibling appears to directly overlap.

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?

The description provides explicit 'Use when' and 'Do not use when' clauses, including conditions about narrower tools, unresolved project scope, or user declination. This clearly guides the AI on when to select this tool over alternatives.

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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