gapup-mcp

deal_coach

Read-only

Coach de deal MEDDIC — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Datadog Enterprise deal Société Générale €1.2M ARR — coaching MEDDIC + escalation plays + 14 next actions. Inputs are validated server-side — send the documented case fields.

Input Schema

TableJSON Schema

Name	Required	Description
`deal`	Yes
`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.
`focus`	No
`knownContext`	Yes
`buyingCommittee`	Yes

TDQS

B3.3/5.0

Behavior4/5

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

The description aligns with annotations: readOnlyHint true (returns a deliverable, no mutations), openWorldHint true (varying results). It adds behavioral context: inputs validated server-side, async option for non-blocking call. No contradiction 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.

Conciseness4/5

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

Description is two sentences plus a reference case, concise and to the point. It front-loads the purpose. Could be slightly more structured (e.g., list of return fields) but overall efficient.

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?

No output schema provided; description only says 'structured, audited deliverable' without specifying contents. For a tool with 5 parameters, nested objects, and no return details, this is incomplete. Missing guidance on what to expect in the result.

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 20% (only 'async' described). The description provides no additional detail on parameters beyond 'send the documented case fields'. The schema defines required objects (deal, buyingCommittee, knownContext) but the description does not explain their semantics or usage, leaving the agent with limited 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 states the tool provides MEDDIC deal coaching and returns a structured deliverable. It references a specific use case (Datadog Enterprise deal). However, it does not explicitly differentiate from similar tools like meddic_scoring or deal_structurer, though the name and focus on coaching provide some distinction.

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

Usage Guidelines3/5

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

The description implies the tool is used for coaching deals with MEDDIC by requiring inputs like deal and buying committee. It mentions server-side validation and documented fields, but lacks explicit guidance on when to use this vs. alternatives (e.g., meddic_scoring for simpler scoring) or when not to use it.

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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