TrendIdea

get_idea_agents

Read-only

Fetch the raw output of the AI agents that analysed an idea (market research, competitor analysis, SWOT, revenue model, legal/IP and 12 more agent types). Pass agentType to zoom in on one agent, or omit it to get every agent result. Read-only and free; use get_idea_summary first if you only need the headline numbers.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`ideaId`	Yes	The idea ID
`agentType`	No	Filter by agent type (e.g. MARKET_RESEARCH, COMPETITOR_ANALYSIS, SWOT_ANALYSIS, REVENUE_MODEL, CFO_AGENT, CMO_AGENT, VC_SCORE, TIMING_ANALYSIS, LEGAL_IP, PATENT_CHECK, EU_SUBSIDY, EXIT_STRATEGY, EXECUTION_PLAYBOOK, PRODUCT_ROADMAP, CONTENT_ENGINE, DNA_FINGERPRINT, PITCH_DECK, BUSINESS_MODEL). Omit for all.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes	The tool result rendered as human and AI readable text or markdown.

TDQS

A4.5/5.0

Behavior4/5

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

Adds value beyond annotations (readOnlyHint=true) by confirming the tool is 'free' and describing the result as 'raw output'. The parameter behavior (omit = all) is explained. No contradictions, but does not disclose potential pagination or size limits.

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?

Two tightly packed sentences cover purpose, parameter usage, and guidance. No redundancy, all information is front-loaded and essential.

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 tool has 2 parameters with high schema coverage, an output schema, and clear annotations, the description provides sufficient context. It explains the raw vs summary distinction and the filtering options, making the tool self-contained.

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

Parameters3/5

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

Schema coverage is 100% and includes a full list of agent types. The description restates the filtering behavior ('zoom in on one agent' vs 'get every agent result') but adds no new semantic information beyond what the schema already conveys.

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 action ('Fetch') and the resource ('raw output of AI agents that analysed an idea'), listing multiple agent categories. It distinguishes from the sibling tool 'get_idea_summary' by contrasting 'raw output' with 'headline numbers'.

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

Usage Guidelines5/5

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

Explicitly tells when to use an alternative ('use get_idea_summary first if you only need the headline numbers') and explains the optional agentType parameter for zooming in or getting all results. Also clarifies the tool is 'Read-only and free', setting expectations.

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

A4.1/5.0

Disambiguation5/5

Each tool targets a distinct function or data aspect, from idea CRUD to simulations, content generation, and team management. Despite the large number, descriptions clearly differentiate purposes, e.g., 'get_idea_summary' vs. 'get_idea_agents' vs. 'get_idea_evolution'. No two tools appear to do the same thing.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (e.g., 'create_idea', 'get_competitive_density', 'toggle_favorite'). No mixing of conventions like camelCase or abbreviations. The pattern is uniform and predictable.

Tool Count2/5

63 tools is far beyond the typical well-scoped range of 3-15. While the platform's broad scope (idea validation, B2B, team, simulations) justifies many, the sheer volume can overwhelm an agent. A more curated subset or grouping would improve coherence.

Completeness5/5

The tool set covers the full startup idea lifecycle: creation, validation, retrieval of various analyses, updates, deletion, sharing, simulations, B2B lead generation, team collaboration, and market intelligence. No obvious gaps exist for the stated domain.

Resources

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