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Glama

Get Onboarding Status

get_onboarding_status

Check what is set up so far and what to do next to get building.

Reports engine_connected / github_connected / project_count / payment_status
and a `next_action` string whose value is authoritative, with this tool
polled between steps. `next_action` is "call_tool" (the tool named in
`next_tool`, with `next_step` describing the call) until onboarding is
complete, then "done". (`next_action_detail` echoes the pre-2026-07-29 dict
shape and is DEPRECATED — it is removed 2026-10-29; next_action/next_tool
are the current fields.)
- engine step: the dashboard /login link goes to the user. Engine
  subscriptions (Claude / Codex / GLM) are connected in the DASHBOARD for
  security — engine credentials are never asked for or pasted in this chat.
- github step: connect_github() returns an install link.
- project step: create_project(...) for a new repo, or
  import_project(repo_full_name) for an existing one.
- launch step: get_provisioning_status(project_id) reports readiness.
Re-checking is the caller's job — the server does not push.
Also returns a `usage` block (pool / daily / machine-hours counters + tier
caps) for capacity-aware automation clients.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With annotations present, the description adds substantial context beyond them: the authority of next_action, the tool's polling semantics, the deprecation window for next_action_detail, and the presence of a usage/capacity block. It does not explain why the annotations mark this status check as non-read-only and non-idempotent, which is the one unexplained behavioral wrinkle.

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 purpose and the authoritative field, then organized into terse per-step bullets. The parenthetical deprecation note is verbose but carries real migration value, so it earns its place; overall density is high with little waste.

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 zero-param status tool with an output schema, this covers everything an agent needs: what is reported, how to interpret next_action, which sibling to call at each step, and the re-poll requirement. Return-value detail is correctly left to the output schema rather than duplicated.

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?

Zero parameters, so per the rubric the baseline is 4. The description appropriately spends no space on parameter documentation and instead clarifies the shape of the returned next_action/next_tool fields.

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 names a specific verb+resource (check onboarding/setup status) and enumerates exactly what is reported: engine_connected, github_connected, project_count, payment_status, next_action, and a usage block. It is clearly distinguishable from siblings like get_provisioning_status or project_status by scoping itself to onboarding progress.

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 states the polling pattern explicitly ('polled between steps'), explains that next_action is authoritative, and maps each onboarding step (engine, github, project, launch) to the sibling tool the agent should call next. It also states the caller must re-check because the server does not push — an unusual but valuable usage constraint.

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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