Generate a personalised cold outreach pitch for a B2B lead using its diagnosis. This calls the LLM and costs tokens; not read-only. Admin only.
| Name | Required | Description | Default |
|---|---|---|---|
| leadId | Yes | The lead 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?
The description discloses that the tool calls the LLM, incurs token costs, and is not read-only, which goes beyond the annotations (readOnlyHint false, idempotentHint true). It also adds an admin-only permission requirement, providing valuable behavioral context.
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?
The description is two concise sentences: the first states the purpose, the second adds critical behavioral and permission caveats. No wasted words, front-loaded purpose.
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?
The tool is relatively simple with one parameter and an output schema. The description covers purpose, cost, read-only status, and admin restriction, making it complete for an agent to decide and invoke correctly.
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 coverage is 100% and the leadId parameter is already described in the schema. The description adds no additional parameter-level detail, so it does not compensate beyond the baseline.
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?
The description clearly states the tool generates a personalised cold outreach pitch for a B2B lead using its diagnosis. It specifies a unique verb+resource combination that differentiates it from general content generation tools like generate_content.
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?
The description implies the tool should be used when a B2B pitch is needed, and it contextually notes that it costs tokens and is admin-only. However, it does not explicitly contrast with alternatives (e.g., generate_content) or provide when-not-to-use scenarios.
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.
