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comp_plan_architect

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Architecture plan de commissionnement — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Gapup Hub — Comp Plan 8 rôles commerciaux · OTE €65-280k · Budget comp €2.1M · Quota coverage 3.2×. 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.
companyYes
targetsYes
geographyNo
salesTeamYes
currentChallengesYes
preferredStructureNo

Schema Changelog

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

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

The description adds that inputs are validated server-side and that the deliverable is structured and audited, which is context beyond the readOnly/openWorld annotations. However, it does not disclose additional behavioral traits such as expected runtime, potential external data usage, or limitations, and the annotations already cover the safety profile.

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 short, but the reference case with specific numbers adds detail that may not be essential for tool invocation. It is generally front-loaded with the purpose, but the reference case could be omitted without losing necessary guidance.

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?

The tool has 7 parameters including nested objects and no output schema, yet the description does not explain the expected deliverable structure or provide details on required fields. It gives a high-level promise of a 'structured, audited deliverable' but not enough for an agent to understand what to send or what to expect in return.

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%, with only the async parameter described. The description merely says 'send the documented case fields,' which does not explain the meaning of fields like company, salesTeam, targets, or currentChallenges, so it 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.

Purpose4/5

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

The name and title indicate commission plan architecture, and the description says it 'Returns a structured, audited deliverable,' implying it generates a comp plan. However, it lacks an explicit verb like 'creates' or 'designs,' and does not differentiate itself from similar tools like revops_architect or comp_benchmark_geo_delta.

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 guidance is provided on when to use this tool versus alternatives. The reference case provides an example use case, but there is no explicit statement of when to choose this tool or when to use another.

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.