List all B2B scouting campaigns with their lead counts and status. Use it to find the campaignId values the other B2B tools need. Read-only and free. Admin only.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| 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 declare readOnlyHint=true, which aligns with 'Read-only' in description. Description adds value by stating 'free' (no cost implications) and 'Admin only' (access control beyond annotations). No contradiction, no behavioral surprises. Minor gap: doesn't disclose if results are paginated or include total counts.
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, 19 words total. Front-loaded with action and resource. Every sentence earns its place: first sentence states capability, second explains utility and constraints. No wasted words.
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 zero parameters, high schema coverage, output schema exists, and simple list operation, description is largely complete. It explains return content (leads, status), purpose (ID discovery), and constraints (read-only, free, admin). Minor gap: no explicit mention of pagination or result ordering behavior.
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 has zero parameters (100% coverage is trivial). Description doesn't need to add param info. It adds meaning about what the list returns ('lead counts and status') and purpose (finding campaign IDs), which is useful semantic context beyond an empty schema.
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 specifies verb 'List', resource 'B2B scouting campaigns', and includes scope details ('with their lead counts and status'). It clearly distinguishes from siblings like 'list_b2b_leads' and 'list_my_ideas' by naming the specific B2B campaign use case.
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?
Explicitly states when to use: 'to find the campaignId values the other B2B tools need', implying it's a prerequisite tool. Also notes 'Read-only and free. Admin only.', covering auth level. No alternative mentioned but context clearly positions it as a discovery tool for downstream B2B operations.
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.
