gapup-mcp

margin_doctor_finance

Read-only

Médecin des Marges — Gapup agent-payable C-suite expertise (CFO). Returns a structured, audited deliverable. Reference case: Alan — ARR €60M · marge brute 68% → 79% · €3,2M fuites identifiées · Rule of 40 : 14→38. 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
`costBreakdown`	Yes
`marginTargets`	Yes
`unitEconomics`	Yes
`incomeStatement`	Yes

TDQS

C2.7/5.0

Behavior3/5

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

Annotations mark it as readOnlyHint=true and openWorldHint=true. The description confirms it returns a deliverable (no mutation), which aligns. However, it does not disclose any further behavioral traits such as authentication needs, rate limits, or what happens with invalid inputs beyond server-side validation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description includes a reference case which may be useful but occupies space. It could be more concise by focusing on core purpose and parameter usage rather than a marketing-like example.

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's complexity (6 parameters, nested objects, no output schema), the description is insufficient. It does not explain the return format, the audit process, or how results are structured. The reference case gives some context but lacks completeness.

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

Parameters1/5

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

The input schema has low documentation coverage (17%) and the description adds no explanation for parameters beyond 'send the documented case fields'. It does not describe the meaning of company, incomeStatement, costBreakdown, etc., leaving the agent to infer from the schema alone.

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 states that the tool returns a structured, audited deliverable for financial margin analysis, and provides a concrete reference case (Alan). However, it does not distinguish itself from the sibling tool 'margin_doctor', causing potential ambiguity about the specific role of 'finance' in its name.

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?

No explicit guidance on when to use this tool versus alternatives like 'margin_doctor' or other financial analysis tools. The description only instructs to 'send the documented case fields', which is procedural rather than selective.

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.

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