gapup-mcp

ftg_business_plan

Read-only

Return the business plan for a market-gap opportunity — direct-trade or local-production, with CAPEX, OPEX, ROI, payback period, automation level and the full plan. Cache-first: returns the stored plan when available, otherwise reports that generation is required (the FTG platform produces plans on demand). When to use this tool: an agent has an opportunity_id (from ftg_market_gap) and needs the investable plan. Input: an opportunity_id.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`async`	No	If 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.
`opportunity_id`	Yes	Opportunity id obtained from ftg_market_gap

Output Schema

TableJSON Schema

Name	Required	Description	Default
`plans`	No
`status`	Yes
`message`	No
`plan_count`	No
`opportunity_id`	Yes

TDQS

A4.5/5.0

Behavior4/5

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

Annotations indicate read-only and open-world behavior. Description adds cache-first behavior and explains that if not cached, it reports generation required. No contradictions; provides useful behavioral context beyond annotations.

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

Conciseness5/5

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

Description is concise and well-structured: first sentence states output and contents, second explains cache behavior, third gives usage guidance. No wasted words, information is front-loaded.

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

Completeness5/5

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

Given the presence of an output schema, the description adequately covers what the tool does, its prerequisites, and behavior. It is complete for a tool that returns a business plan and fits within the suite of ftg tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value by clarifying that opportunity_id comes from ftg_market_gap, which is crucial for correct usage. Async parameter is already well-described in schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

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

The description clearly states the tool returns a business plan for a market-gap opportunity, listing included elements (CAPEX, OPEX, ROI, payback period, automation level) and distinguishing it from siblings by specifying it uses opportunity_id from ftg_market_gap.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: when an agent has an opportunity_id and needs the investable plan. Also mentions cache-first behavior. Could be more explicit about when not to use, but the context is clear.

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

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

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