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enps_auto

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eNPS automatisé — Gapup agent-payable C-suite expertise (CHRO). Returns a structured, audited deliverable. Reference case: BlaBlaCar — eNPS pulse mensuel · 700 FTE 8 pays · segments × tenure × manager · plays correctifs ciblés. 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.
focusNo
companyYes
contextYes
toolStackYes
segmentationYes
presenterScriptNo

TDQS

B3.1/5.0
Behavior3/5

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

The description adds useful behavioral context: it returns a deliverable, the deliverable is audited, and inputs are validated server-side. Since the readOnlyHint is already provided, the description doesn't need to re-state safety, but it doesn't disclose async behavior, error handling, or pagination, so it only partially passes the transparency burden.

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 short (three sentences) and front-loaded with the tool's purpose. The reference case is an efficient way to convey expected usage, though the phrase 'Gapup agent-payable C-suite expertise' is jargon that adds little concrete meaning. Overall it is concise but not maximally clear.

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, deep nesting, no output schema) and the low schema description coverage, the description is insufficient. It does not describe the shape of the returned deliverable, how to use the async parameter, or what the required nested fields mean. The brief validation note and reference case are not enough to make the tool safely invocable.

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 does not compensate. It mentions 'segments × tenure × manager,' which hints at segmentation fields, but it does not explain the structure or meaning of the nested required parameters (company, context, toolStack, segmentation). The instruction to 'send the documented case fields' assumes external documentation that is not present in the schema or description.

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 identifies the domain (eNPS) and states that it returns a structured, audited deliverable, which sets it apart from general HR tools. However, it lacks a strong imperative verb like 'generates' or 'builds' and includes vague phrasing ('Gapup agent-payable C-suite expertise'), preventing a perfect score.

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 reference case (BlaBlaCar, eNPS pulse mensuel, 700 FTE, 8 pays) implies a concrete scenario, giving the agent some context for when to use it. But there is no explicit statement of when to use this tool versus alternatives, no exclusions, and no mention of prerequisites beyond 'documented case fields.'

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.