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onboarding_salaries

Read-only

Onboarding opérationnel des salariés — Gapup agent-payable C-suite expertise (COO). Returns a structured, audited deliverable. Reference case: Pennylane (FR fintech SaaS, ~250 FTE) — 5 parcours 30/60/90 jours · Engineering / Sales / CS / Design / People Ops. 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
rolesYes
companyYes

Schema Changelog

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

  1. First observed

TDQS

C2.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows this is a safe read operation. The description adds that it returns an 'audited deliverable' and that inputs are 'validated server-side', which provides some extra behavioral context. However, it does not describe the output structure, any potential side effects, or what 'audited' means in practice. No contradiction with annotations found.

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

Conciseness2/5

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

The description is relatively short, but it is not front-loaded with a clear functional statement. It mixes French and English, includes a specific reference case that may not be relevant to all users, and uses jargon like 'Gapup agent-payable C-suite expertise (COO)' without explanation. Every sentence does not earn its place; the reference case could be omitted in favor of a clearer general description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a complex tool with nested objects, 4 parameters, and no output schema. The description fails to explain what the deliverable actually contains, how to interpret the 'roles' array, what 'parcours 30/60/90 jours' means, or what the expected output format is. Given the complexity, the description is severely incomplete and leaves the agent without enough information to correctly invoke the tool.

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?

Schema description coverage is only 25% (only the 'async' parameter has a description). The description does not explain the meaning or expected format of 'company', 'roles', or 'focus'. The phrase 'send the documented case fields' is unhelpful and does not clarify what parameters are needed or how to structure them. The tool fails to compensate for the low schema coverage.

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 it is about 'Onboarding opérationnel des salariés' and says it returns a 'structured, audited deliverable', giving some sense of the tool's function. However, it lacks a clear, direct statement of what the tool does beyond this vague phrase, and does not distinguish it from sibling tools like 'comp_plan_architect' or 'talent_intelligence'. The reference to 'Pennylane' and '5 parcours 30/60/90 jours' hints at onboarding pathway generation but remains unclear.

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 provides no explicit guidance on when to use this tool versus alternatives. It mentions a specific reference case and says 'send the documented case fields', but does not explain in which scenarios this tool is appropriate or what distinguishes it from other HR/talent tools. The usage context is only implied by the tool's name and the reference case.

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.