Get B2B lead engine statistics - campaigns, leads and conversion rates - for a performance overview. Read-only and free. Admin only.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
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| 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?
The description supplements the annotations by confirming read-only behavior and adding that the tool is free and admin-only. This provides additional context beyond the structured annotations, such as cost and authorization requirements. 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?
Two sentences efficiently convey purpose, scope, and constraints. Every sentence adds value: the first states what it does, the second covers permissions and safety. No fluff or redundancy.
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 no parameters and an existing output schema, the description covers the essential behavioral and access context. However, it lacks mention that this tool provides aggregated vs. detailed data, which would help agents decide between this and list siblings. Still, it is largely complete for a simple read-only endpoint.
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?
With zero parameters, the input schema is fully covered. The description adds meaningful context by listing the data categories (campaigns, leads, conversion rates) that will be returned. Since there is an output schema, detailed return value descriptions are not required. The baseline for zero-param tools is 4, and the description meets that.
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 it retrieves B2B lead engine statistics covering campaigns, leads, and conversion rates for a performance overview. The verb 'get' and resource are specific. However, it does not explicitly distinguish itself from sibling tools like list_b2b_campaigns or list_b2b_leads, which could also serve similar purposes but at a different granularity.
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?
No explicit guidance on when to use this tool versus the many list-oriented siblings (e.g., list_b2b_campaigns, list_b2b_leads). The description only notes access restrictions (Admin only) and safety (Read-only), but fails to clarify that this tool provides aggregated overview data rather than raw lists, which is a key differentiation.
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.
