Skip to main content
Glama

mcp-knowledge

by io.github.getgapup

budget_variance_ai

Read-only

Analyse d'écart budgétaire — Gapup agent-payable C-suite expertise (CFO). Returns a structured, audited deliverable. Answers: Explain the key drivers of the budget vs actual variance for in — what are the top 10 narrative explanations? · Which cost categories drove the budget overrun for in , and what corrective actions should management take? · Revise the Q4 forecast based on observed Q3 variances for — give me 3 scenarios (base, optimistic, conservative). · Prepare a board-ready budget variance memo for — , budget €M vs actual €M, with management actions. · What are the quick wins to reduce budget overspend for by end of quarter without impacting growth targets? Reference case: Doctolib Q3 2026 — budget €38.5M vs actual €41.2M (+7.0%) — cloud + headcount + deals timing. 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
entityYes
budgetContextYes

TDQS

B3/5.0
Behavior3/5

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

Annotations indicate readOnlyHint=true and openWorldHint=true, which are consistent with a read-only analysis tool. The description adds that it returns a 'structured, audited deliverable' and validates inputs server-side, but does not mention async behavior (despite an async parameter in the schema) or other operational details like rate limits.

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 paragraph that includes a list of example questions. It front-loads the core purpose, but the inclusion of multiple examples makes it longer than necessary. It is adequately structured but could be more concise.

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 nested objects and 4 parameters, but the description does not explain the return format beyond 'structured, audited deliverable', nor does it clarify the async functionality or the required fields. Given the absence of an output schema, the description should provide more detail about what the agent can expect as a result.

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 25% (only the async parameter has a description). The description mentions placeholders like <company> and <period> in example questions, which hint at entity fields, but it does not formally explain the structure or required fields of entity and budgetContext. This leaves the agent with insufficient guidance for constructing valid inputs.

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 states the tool performs 'Analyse d'écart budgétaire' (budget variance analysis) and provides specific example questions that illustrate its purpose. However, it does not explicitly differentiate itself from sibling tools like margin_doctor_finance or financial_model_3statement, which may have overlapping capabilities.

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 description provides several example queries that imply when to use the tool (e.g., explaining drivers, revising forecasts, producing board memos). However, it offers no explicit guidance on when not to use it or which alternative tools might be better suited for other scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All mcp-knowledge toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

Resources