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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

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It adds important behavioral context: scoping to 'THIS workspace', recency ordering, and the default status filter ('default new'). However, it doesn't disclose what constitutes an 'engagement event', whether pagination exists, or any rate limits. This is adequate but not rich.

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?

Two sentences, front-loaded with usage triggers, and no filler. Every sentence serves a purpose: trigger phrases, output description, filtering, and pairing. Extremely concise and well-structured.

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?

Given no output schema and no annotations, the description covers the essentials: purpose, usage triggers, scoping, ordering, filter options, and a workflow recommendation. It could be slightly more explicit about the return format (e.g., list of events with fields), but for a simple list tool it is reasonably 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 75% (workspaceId lacks a description). The description adds meaning to workspaceId by specifying 'for THIS workspace', and it reinforces the status filter values. However, it doesn't elaborate on limit or sinceHours beyond what the schema already says. Since the schema does most of the heavy lifting, a 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 clearly states the tool's function: 'Returns engagement events for THIS workspace, ordered by recency.' It provides specific example user queries ('what came in from my launches?', 'show me my replies') that make the purpose unmistakable. The verb 'returns' plus the resource 'engagement events' distinguishes it from sibling tools like chieflab_launch_product or chieflab_draft_reply.

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 opens with 'USE WHEN' and lists exact user phrasings that should trigger this tool, providing clear when-to-use guidance. It also recommends pairing with chieflab_draft_reply for handling the events, which guides the agent on workflow. This is explicit and actionable.

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.

Resources