gapup-mcp

win_loss_decoder

Read-only

Analyse Win/Loss deals — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Gapup Hub — Win/Loss 32 deals Q1 2026 · Win rate 41% → 68% potentiel · Playbook 8 actions CRO. 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.
`deals`	Yes
`company`	Yes
`product`	Yes
`topCompetitors`	No
`primaryChallenge`	No
`salesCycleTargetDays`	No

TDQS

C2.9/5.0

Behavior3/5

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

Annotations already provide readOnlyHint and openWorldHint, so the description adds minimal value. It mentions server-side validation and an 'audited deliverable', but lacks details on rate limits, auth needs, or side effects.

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 relatively concise and front-loads the core purpose, though the inclusion of specific percentages and case details adds slight verbosity without critical value.

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 (7 parameters, nested objects, no output schema), the description omits crucial details such as the return format, required vs optional fields, and how to interpret the structured deliverable.

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 low (14%), and the description does not elaborate on parameter meanings beyond 'send the documented case fields'. It fails to compensate for the lack of schema descriptions.

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 analyzes win/loss deals and returns a structured, audited deliverable, with a specific reference case. However, it does not distinguish itself from similar sibling tools like deal_coach or competitor_intel.

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 mentions 'send the documented case fields' but provides no guidance on when to use this tool versus alternatives, nor does it specify 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.

Resources

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