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upsell_hunter

Read-only

Chasseur d'upsell — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Gapup Hub — Upsell 8 comptes · €127k potentiel · Top 3 : Alan+Qonto+Pennylane · Playbook 5 étapes. 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
horizonNo
productYes
accountsYes
targetUpsellEurNo

Schema Changelog

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

  1. First observed

TDQS

C2.8/5.0
Behavior3/5

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

Annotations indicate readOnlyHint=true and openWorldHint=true, so the agent knows this is a safe read operation with variable output. The description adds that it returns a 'structured, audited deliverable' and that inputs are validated server-side, which is useful context beyond the annotations. However, it doesn't disclose other behavioral traits such as potential delays, output size, or any prerequisites beyond field validation, so it adds moderate but not rich context.

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 a single sentence but includes some clutter like 'Gapup agent-payable C-suite expertise (CRO)' that may distract rather than inform. It front-loads the core purpose and includes a reference case, which is useful, but the phrasing is not maximally clean. It earns a middle score for being moderately concise but not fully streamlined.

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 (6 parameters, nested objects, no output schema), the description is incomplete. It says it returns a 'structured, audited deliverable' but does not detail the structure or fields of that deliverable. The reference case gives a glimpse, but it is not a formal description. Input semantics are also largely omitted. The agent would need additional information to invoke this tool correctly.

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 17% (only 'async' has a description). The description mentions 'send the documented case fields' but does not explain any of the parameters (company, product, accounts, horizon, targetUpsellEur) or their semantics. This falls short, as the schema leaves most parameter meanings implicit and the description does not compensate for the low 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 description clearly identifies the tool as an 'upsell hunter' providing C-suite expertise for CRO, and states it 'Returns a structured, audited deliverable.' The reference case (e.g., 'Upsell 8 comptes · €127k potentiel · Top 3 : Alan+Qonto+Pennylane · Playbook 5 étapes') provides a concrete example of the output, giving clear scope. However, it does not explicitly differentiate from sibling tools like cross_sell_reco or account_expansion_mapper, so it misses the top distinction.

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 gives no explicit guidance on when to use this tool versus alternatives. It includes 'Inputs are validated server-side — send the documented case fields,' which is an input instruction rather than usage context. There are no exclusions or mentions of alternative tools for different scenarios, so it falls into 'no guidance' territory.

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.