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by io.github.bdentech

chieflab_approve_action

[chieflab_* alias of chiefmo_approve_action] Approve one ChiefMO publish/send action so its executor can fire. USE WHEN the user — in IDE chat — said 'approve ' (e.g. 'approve linkedin', 'approve hn'), 'approve all', 'ship it', 'go ahead', or otherwise greenlit a specific draft you rendered. Match the user's words to the channel, look up agentGuide.renderInChat[channel].actionId from the launch response, and call this tool with that actionId. This is the IDE-native approval path — no need to push the user to the reviewUrl. Pass actionId (preferred) or id (legacy alias). P74: pass autoExecute: true AND the connector inputs (platforms for social / recipients + subject for email) to have the approval chain directly into execution — approve and ship in one tool call. Without autoExecute (or when connector is manual_handoff / blocked), the response includes executionPlan and the caller is expected to invoke the suggestedTool next.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoLegacy alias for actionId.
subjectNoP74. For autoExecute on email: subject line override.
actionIdNoThe action id from publishActions[].id in a launch_product response. Preferred.
mediaUrlsNoP74. Optional media URLs for the social post — auto-uploaded to Zernio's CDN before publishing.
platformsNoP74. For autoExecute on social channels: Zernio platform descriptors, e.g. [{platform: 'linkedin', accountId: '<id>'}]. Required when autoExecute=true and mode=oauth_connector.
recipientsNoP74. For autoExecute on email: recipient email addresses.
autoExecuteNoP74. When true AND the action's executionMatrix.mode is oauth_connector / api_key_connector / native_api AND the connector is ready, the approve handler immediately invokes chieflab_execute_approved_action with the inputs you supply. The response includes the executor result + the unified proof ledger. Defaults to false (preserves the prior contract — agent calls execute_approved_action explicitly).

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries the full transparency burden, and it succeeds. It discloses the approval side effect, the autoExecute path that invokes chieflab_execute_approved_action, the default false behavior, and the response's executionPlan/suggestedTool when autoExecute is not used. It also notes when the connector is manual_handoff or blocked, providing richer behavioral context than a simple 'approve' would.

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 dense and lengthy, but the complexity of the tool justifies most of the length. It front-loads the purpose and use case, then provides the necessary workflow and parameter context. A slight deduction is warranted because some details, such as P74 references, could be clearer or more tightly integrated.

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 the tool's complexity, no output schema, and many optional parameters, the description covers the full workflow: when to call, how to find the action ID, the IDE-native path, the autoExecute behavior and conditions, and the expected next step when autoExecute is not used. It is sufficiently complete for an agent to select and invoke the tool correctly in most scenarios.

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 schema already covers all 7 parameters with 100% coverage, so the baseline is 3. The description adds value by emphasizing actionId as preferred and id as a legacy alias, and by explaining how platforms/recipients/subject are used together with autoExecute. This goes beyond a simple restatement of parameter names.

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 uses a specific verb ('Approve') and resource ('one ChiefMO publish/send action') and clearly distinguishes this from sibling tools like chieflab_execute_approved_action and chieflab_publish_approved_post. It also explains the IDE-native approval path and how it differs from pushing the user to reviewUrl.

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 explicitly states when to use the tool ('USE WHEN the user said approve <channel>, approve all, ship it, go ahead'), and gives a precise procedure for finding actionId from agentGuide.renderInChat. It also explains when autoExecute is appropriate and what to do without it, making alternatives and expected next steps 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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