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ChiefLab

by io.chieflab.api

chieflab_inbox

USE WHEN the user asks 'what came in from my launches?' / 'show me my replies' / 'what's in my inbox?' / 'who responded to the LinkedIn post?'. Returns engagement events for THIS workspace, ordered by recency. Filter by status (new / drafted / approved / sent / dismissed) — default new. Pair with chieflab_draft_reply to handle them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax events to return. Default 50.
statusNonew | drafted | approved | sent | dismissed | all (default: new)
sinceHoursNoOnly events received in the last N hours. Default 168 (7 days). Max 720 (30 days).
workspaceIdNo

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It only states returns events with filtering, but does not confirm read-only nature, side effects, permissions, or error behavior. This is insufficient for a safe tool invocation.

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 concise, front-loaded sentences with zero wasted words. Every sentence adds value: usage triggers, core functionality, and pairing advice.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite moderate complexity (4 params, no output schema), the description does not explain the output structure, pagination behavior, or error handling. This leaves critical gaps for an agent to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 75%, but the description adds no extra meaning beyond the schema for the three documented parameters. The workspaceId parameter lacks description in both schema and tool description, leaving a gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verb 'returns' and resource 'engagement events' with example queries, clearly indicating what the tool does. It is distinct from siblings but does not explicitly differentiate from alternatives, so it stops short of a 5.

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 explicitly states when to use (e.g., 'what came in from my launches?') and pairs with chieflab_draft_reply, providing clear context. However, it lacks explicit exclusions or alternative tools for unrelated queries.

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.

Resources