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discovery_prep

Read-only

Préparation discovery — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Discovery Salesforce × Airbus — VP Digital Marc Legrand · Signaux achat confirmés · +28 pts conversion demo. Inputs are validated server-side — send the documented case fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf 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.
contactYes
ourOfferYes
prospectYes
meetingGoalNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and openWorldHint, so the description need not repeat those. It does add that the deliverable is structured and audited and that inputs are validated server-side, which is useful but limited; no response format, auth needs, or rate limits are disclosed.

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 is relatively short but includes marketing-flavored content like 'Gapup agent-payable C-suite expertise (CRO)' and a reference case that do not directly aid tool invocation. It front-loads the nominal purpose and output, but the structure mixes French and jargon without a clear functional breakdown.

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?

With 5 parameters, nested objects, and no output schema, the description fails to specify required input structure, parameter semantics, or deliverable format. It leaves the agent dependent on undocumented 'documented case fields,' which is inadequate for confident, correct invocation.

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 20% (only 'async' is described), but the description provides no meaningful parameter-level guidance beyond the vague 'send the documented case fields.' The agent cannot infer how to populate prospect, contact, ourOffer, or meetingGoal from this text.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states that the tool prepares a discovery and returns a structured, audited deliverable, but it uses the noun phrase 'Préparation discovery' rather than a clear action verb. The Salesforce × Airbus reference adds color but does not clearly differentiate the tool from sibling sales enablement tools like meddic_scoring or deal_coach.

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 when-to-use or when-not-to-use guidance is provided. The reference case and 'send the documented case fields' hint at a discovery context, but the agent is not told when to choose this tool over alternatives or what prerequisites exist.

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

C2.4/5.0
Disambiguation1/5

Over 50 tools share the identical template 'Gapup agent-payable C-suite expertise' with similar French descriptions and reference cases, making their boundaries indistinguishable. Clusters like competitor_intel, competitive_deep_dive, competitor_moves, competitor_profiles, competitor_pricing_radar, competitor_pricing_scrape, and competitor_recommendations heavily overlap in purpose.

Naming Consistency1/5

Names are chaotic: mix of French and English, snake_case and camelCase, verb_noun, noun, and adjective forms with no uniform pattern. Examples like 'bp_narratif', 'content_enrichment', 'ai_governance_full_report_async', and 'job_result' show no coherent naming convention.

Tool Count1/5

271 tools is far beyond any reasonable MCP server scope, creating an overwhelming selection burden for agents. This count vastly exceeds the 25+ threshold for 'too many' and makes navigation impractical.

Completeness2/5

While the server covers many business domains, it lacks lifecycle operations (e.g., no update/delete tools for the deliverables it generates) and the input specifications are vague ('documented case fields' without documentation), creating functional dead ends. The sheer breadth does not compensate for these gaps.