ChiefLab

chieflab_verify_install

POST-INSTALL HEALTH CHECK. Call this exactly once after the agent has wired ChiefLab into the runtime (per the bootstrap protocol at https://chieflab.io/bootstrap.txt). Returns { ok, mcpReachable, toolsDiscovered, visibleFrontDoorTools, callableInternalTools, workspaceReady, hasOpenLoops, blockedConnectors, summary }. toolsDiscovered means the visible front-door catalog, not every internal/back-compat callable handler. The summary is one sentence the agent should paste verbatim to the user — e.g. 'ChiefLab installed and ready. Workspace fresh, no open loops, all channels need connectors before auto-publish.' Do NOT list every internal tool — render the summary only. If ok is false, the response includes a nextStep describing the single recovery action.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`workspaceId`	No	Optional workspace id; inferred from bearer auth.

TDQS

A4.1/5.0

Behavior4/5

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

Describes the return object in detail, clarifies ambiguous fields (e.g., toolsDiscovered), specifies error behavior (nextStep on false ok), and explains parameter inference. Given no annotations, it provides substantial behavioral disclosure.

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?

Well-structured: starts with purpose, then usage, return fields, clarifications, and error handling. All sentences are necessary given the complexity of the return object.

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?

Covers purpose, usage, return structure with field explanations, and error recovery. Without an output schema, it provides enough detail for correct agent invocation.

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?

The schema already documents the single parameter with 100% coverage. The description restates the parameter's optionality and inference without adding new meaning beyond the schema.

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 'POST-INSTALL HEALTH CHECK' and specifies the exact timing (call once after wiring ChiefLab). It distinguishes from sibling tools by its unique post-install role.

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?

Explicitly says 'Call this exactly once after the agent has wired ChiefLab into the runtime' and references a bootstrap protocol. Provides clear context, though does not mention alternatives or when not to use.

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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TDQS

A3.7/5.0

Disambiguation4/5

Most tools have distinct purposes, e.g., approve_action vs execute_approved_action vs publish_approved_post. However, alias overloading (e.g., chieflab_launch_product and chieflab_get_users_after_build pointing to the same handler) introduces some ambiguity. The detailed descriptions mostly mitigate confusion, but an agent might still struggle to choose between near-identical aliases.

Naming Consistency4/5

Tools predominantly follow a 'chieflab_verb_noun' pattern (e.g., chieflab_approve_action, chieflab_connect_provider). A few exceptions exist (chieflab_help, chieflab_inbox, chieflab_boot) that are single nouns, but these are clearly distinct and the overall consistency is high.

Tool Count3/5

32 tools is on the high side for an MCP server, but the domain of a growth/marketing launch platform naturally requires many operations (launch, approve, execute, measure, iterate, connect providers, etc.). The count is borderline but still manageable; it doesn't reach the 50+ extreme.

Completeness4/5

The tool set covers the full launch lifecycle: create, approve, execute, measure, and iterate. It includes provider connections, manual fallback, brain summary, and work requests. Minor gaps exist (e.g., no explicit tool for deleting a launch or revoking approval), but core workflows are fully supported.

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