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chieflab_get_publishing_targets

P79 — read the workspace's stored publishing target defaults. Returns { channelTargets, store }. Useful before launch so the agent can surface 'You haven't connected an Instagram account yet — set it via chieflab_set_publishing_targets' instead of blocking on first auto-execute.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceIdNoOptional workspace id.

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states this is a read operation ('read'), describes the return value ('Returns { channelTargets, store }'), and indicates it reads stored defaults. It does not mention error cases or side effects, but for a simple getter, this is adequate. No contradictions with annotations.

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 two sentences: the first states the core function, and the second provides a practical use case with a concrete example message. It is front-loaded, concise, and every sentence earns its place without unnecessary detail.

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?

For a simple getter with one optional parameter and no output schema, the description is complete: it states what is read, what is returned, and when to use it (before launch). It even provides a sample user-facing message, making its role in the larger workflow clear. Given the low complexity, no further details are needed.

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?

The schema has 100% description coverage for its one parameter, 'workspaceId' described as 'Optional workspace id.' The description beyond the schema mentions 'the workspace's stored publishing target defaults,' which slightly clarifies the parameter's role, but adds little new semantics. Baseline 3 is appropriate given schema coverage.

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: "read the workspace's stored publishing target defaults." It specifies the verb 'read' and the resource 'publishing target defaults,' and distinguishes it from sibling chieflab_set_publishing_targets by indicating this is a read operation. The returned shape '{ channelTargets, store }' adds further specificity.

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 provides a concrete usage scenario: 'Useful before launch so the agent can surface... instead of blocking on first auto-execute.' It implies when to use (prior to launch) and references the sibling for setting targets, which helps differentiate. However, it does not explicitly state when not to use it or describe alternative tools beyond the one sibling.

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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