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ftg_business_ideas

Read-only

Return vetted, automation-scored business ideas from the FTG idea bank — each with an autonomy score, monetization model and conservative/median/optimistic MRR projections. When to use this tool: an agent or founder wants ranked, buildable business ideas. Input: optional category and limit.

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.
limitNo
categoryNoOptional category filter

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
ideasYes

TDQS

A4.1/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true and openWorldHint=true, so the safety profile is already clear. The description adds useful behavioral context by detailing the output structure (autonomy score, monetization model, MRR projections) and conveys a read-only, retrieval operation. It does not contradict 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?

The description is two concise, well-structured sentences. It front-loads the core purpose, then provides usage context and input hints, with no filler or redundant information.

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

Completeness4/5

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

For a simple list retrieval tool with 0 required parameters and an output schema (not shown), the description adequately covers purpose, usage, input, and expected output. It misses only minor aspects like async behavior, which is already documented in the schema, so the description is reasonably complete.

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 67% (async and category are described, but limit lacks a description). The description only says 'optional category and limit', which merely names the parameters without adding explanatory meaning. It does not clarify limit's behavior or any additional parameter constraints beyond schema basics.

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 'Return vetted, automation-scored business ideas from the FTG idea bank', specifying the exact resource and purpose. It distinguishes itself from siblings like ftg_market_gap and ftg_opportunity_scout by emphasizing ranked, buildable ideas with specific scoring.

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?

Provides explicit context: 'When to use this tool: an agent or founder wants ranked, buildable business ideas.' This clearly indicates the intended scenario, though it lacks explicit exclusions or alternative tool references.

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.