gapup-mcp

capacity_planning

Read-only

Planification capacitaire — Gapup agent-payable C-suite expertise (CHRO). Returns a structured, audited deliverable. Reference case: Gapup Hub — 22→48 FTE en 12m · ARR €480k→€1.7M · Plan d'embauches par département. Inputs are validated server-side — send the documented case fields.

Input Schema

TableJSON Schema

Name	Required	Description
`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.
`company`	Yes
`benchmarks`	No
`financials`	Yes
`constraints`	No
`currentTeam`	Yes
`hiringBudgetEur`	No

TDQS

C2.9/5.0

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 inputs are validated server-side, implying error handling behavior. It does not contradict annotations, but it adds minimal behavioral context beyond what annotations provide.

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 brief (3 sentences) but mixes French and English, which may reduce clarity for some agents. It front-loads the purpose and includes a reference case, but the language mixing is a minor structural flaw.

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?

Given the tool has no output schema, complex nested inputs, and 7 parameters, the description is insufficient. It doesn't describe the deliverable's structure, how to interpret results, or any expected response format. The reference case hints at outcomes but not structure.

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 description coverage is only 14%, and the description contributes no parameter-level meaning. It vaguely says 'send the documented case fields' but doesn't list or explain parameters. The schema's own descriptions for nested objects are sparse, leaving the agent with little guidance.

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 clearly indicates the tool is for capacity planning for CHROs, mentioning it returns a structured, audited deliverable and providing a reference case. The French title and description reinforce the specific domain, though it lacks a single verb+resource phrase. The purpose is distinct from sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives like 'capital_strategy' or 'growth_path_architect'. It only asserts inputs are validated server-side, which is a technical note, not usage context. No exclusions or examples of when not to use.

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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