Return the full evolution history of an idea: VC score changes over time, edit history and version tracking. Use it to understand how an idea has improved or drifted since creation. Read-only and free; pass an ideaId you own.
| Name | Required | Description | Default |
|---|---|---|---|
| ideaId | Yes | The idea ID |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes | The tool result rendered as human and AI readable text or markdown. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, so the description reinforces this with 'Read-only and free'. Adds behavioral context about ownership requirement ('pass an ideaId you own') and the nature of returned data (history of changes). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each dense with useful information: purpose, use case, and constraints. No fluff or repetition. Front-loaded with the core action and then details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is only one simple parameter, a descriptive output schema, and full annotations, this description is fully adequate. It covers what the tool does, why to use it, and how to use it without gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the parameter's purpose in context: 'pass an ideaId you own' clarifies the parameter must be an idea owned by the user, which is not explicit in the schema's minimal 'The idea ID' description. This extra context raises the score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool returns 'full evolution history of an idea' with specific examples like 'VC score changes over time, edit history and version tracking'. It distinguishes itself from sibling get_* tools like get_idea_timeline and get_improvement_synthesis by focusing on evolution history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
States when to use it: 'to understand how an idea has improved or drifted since creation'. Also notes it is 'Read-only' and 'free', and specifies requirement: 'pass an ideaId you own'. No explicit when-not-to-use or alternatives, but the use case is clear and helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.
