ChiefLab

chieflab_create_next_move_action

P75 — turn a Next Move suggestion into an approval-gated draft action. USE WHEN you've called chieflab_suggest_next_move and the suggestion's kind is not 'wait' or 'noop'. Creates an actionStore entry with status='awaiting_approval', the suggested draft body inline, and an executionMatrix that points at the right next-execution path. The reviewer sees the new card in the Launch Room / IDE chat like any other approval card — same approve / revise / reject flow. Closes the loop: launch → measure → next move → approve → execute → repeat.

Input Schema

TableJSON Schema

Name	Required	Description
`runId`	Yes	Required. The originating run id (the next-move action is tagged with this so the brain can compound launch → measure → next-move chains).
`channel`	Yes	Channel the measurement was for (used to ground the suggestion).
`metrics`	Yes	Same metrics object passed to chieflab_suggest_next_move.
`workspaceId`	No	Optional workspace id.

TDQS

A4.9/5.0

Behavior5/5

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

No annotations present; description fully details behavior: status='awaiting_approval', inline draft body, executionMatrix, and that it uses same approve/revise/reject flow as other cards.

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?

Front-loaded with a clear one-line summary, then expands systematically. Every sentence adds essential info without redundancy.

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?

No output schema, but description explains what is created (action entry with status, draft, matrix). Also ties into sibling tools for approval and execution, making the overall process clear.

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 coverage is 100% so baseline 3. Description adds value by explaining runId chains launches, channel grounds suggestion, metrics is same as suggest function. WorkspaceId noted as optional.

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?

Clearly states verb 'turn' and resource 'Next Move suggestion' into 'approval-gated draft action'. Distinguishes from sibling tools like chieflab_suggest_next_move and chieflab_approve_action.

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?

Explicit precondition: call after chieflab_suggest_next_move when suggestion kind is not 'wait' or 'noop'. Also describes the reviewer flow and closure of the loop.

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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