ChiefLab

chieflab_skip_next_move

P142 — founder rejects a next-move recommendation without doing it. Captures a reason so the brain learns which kinds of moves don't fit this workspace (e.g. 'we don't cross-post to Reddit on principle' / 'we tried DMs already'). Flips action to rejected with metadata.skipReason. The next-move generator reads recent skip reasons before suggesting moves of the same kind on this workspace.

Input Schema

TableJSON Schema

Name	Required	Description
`reason`	No	Why the founder is skipping this. Used by the brain to avoid suggesting similar moves.
`actionId`	Yes	The next-move action id.
`workspaceId`	No	Optional workspace id.

TDQS

A4.4/5.0

Behavior5/5

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

With no annotations provided, the description carries full behavioral disclosure. It reveals the side effect (flips action to rejected with metadata.skipReason) and explains the feedback loop to the brain. This goes beyond the bare minimum and is genuinely transparent about state changes and future behavior.

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?

The description is three sentences, each serving a purpose: stating the action, explaining the reason capture, and describing the effect. It is front-loaded and contains no filler.

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?

The tool is simple (3 params, no output schema), and the description covers its purpose, side effects, and downstream usage. It does not address edge cases like invalid actionId, but given the low complexity, the description is nearly complete.

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?

Schema description coverage is 100%, so each parameter already has a description. The tool description adds context for the 'reason' parameter with examples of appropriate reasons, but it doesn't significantly extend the meaning of actionId or workspaceId. Baseline 3 is appropriate.

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 states a specific verb ('rejects') and resource ('next-move recommendation'), and clearly differentiates from sibling tools like approve or execute actions. It explicitly notes the action is not done and flips to rejected, leaving no ambiguity about its purpose.

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?

The description clearly indicates when to use the tool: when a founder rejects a next-move recommendation. It explains the downstream effect on the generator, which implies the value of capturing reasons. However, it doesn't explicitly name alternatives or state when not to use it, though the context is clear.

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

A3.8/5.0

Disambiguation2/5

Many tools have overlapping purposes (e.g., multiple launch and measurement tools), and the presence of aliases like chiefmo_* can confuse an agent. While descriptions are detailed, the sheer number of tools covering similar workflow steps makes it hard to distinguish the right one without careful reading.

Naming Consistency4/5

All public tools start with 'chieflab_' and mostly follow a verb_noun pattern (e.g., chieflab_approve_action, chieflab_set_company_profile). However, some internal names like 'chiefmo_*' appear as aliases, which slightly breaks consistency from the user's perspective.

Tool Count1/5

45 tools is excessive for a single MCP server. While the domain is broad, this many tools likely overwhelms agents and users. Most well-scoped servers have 3-15 tools; 45 indicates poor scoping and should be split into focused sub-servers.

Completeness5/5

The tool surface is extremely comprehensive, covering the full lifecycle from signup and installation to launch, approval, execution, measurement, next-move suggestions, manual fallback, and specialist delegation. No obvious gaps for the stated purpose of growth and distribution.

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