gapup-mcp

content_taxonomy

Read-only

Return the enrichment taxonomy of a content domain — every tag grouped by facet (genre, theme, mood, play-mode…). When to use this tool: an agent needs the controlled vocabulary to filter, classify or query content. Input: a domain.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`async`	No	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
`domain`	Yes	Content domain

Output Schema

TableJSON Schema

Name	Required	Description
`domain`	Yes
`taxonomy`	Yes	Map facet → array of tag labels
`tag_count`	Yes
`facet_count`	Yes

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds that it returns a taxonomy but does not elaborate on additional behavioral traits beyond what the annotations provide. No contradictions.

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, concise and front-loaded with the purpose. Every sentence adds value: the first explains the result, the second explains when to use it. No wasted words.

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 the tool's simplicity (2 params, enum domain, output schema exists), the description covers purpose, usage, and input. It does not discuss error conditions or performance, but these are not critical for a straightforward read-only lookup.

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 coverage is 100%, so the baseline is 3. The description mentions 'Input: a domain' which is redundant with the schema. It does not add meaning for the 'async' parameter, but the schema itself is sufficient.

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 explicitly states 'Return the enrichment taxonomy of a content domain — every tag grouped by facet (genre, theme, mood, play-mode…)', providing a specific verb+resource and distinguishing this tool from sibling tools that deal with content but not taxonomy.

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 includes an explicit 'When to use this tool: an agent needs the controlled vocabulary to filter, classify or query content.' This clearly defines the context, though it lacks explicit when-not-to-use or alternatives, which are not critical here.

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

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources

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