Get scouting info for a campaign: the existing lead count and instructions for triggering new scouts. Use it before kicking off a scouting run. Read-only and free.
| Name | Required | Description | Default |
|---|---|---|---|
| campaignId | Yes | The campaign 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 declare readOnlyHint=true, so the description's added value is limited. However, it reinforces the read-only nature and adds the 'free' qualification (no cost), which goes beyond annotations. No contradictions are present. The description does not detail additional behavioral traits like rate limits or data freshness.
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 incredibly concise at two sentences, front-loading the core purpose and then providing usage guidance. Every sentence earns its place with 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 the tool has only one simple parameter, full schema coverage, a clean annotation, and an output schema, the description is complete enough. It tells the agent what it returns (lead count, scout instructions), when to use it, and its safety profile. No gaps remain for the agent to be confused.
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% with the parameter 'campaignId' already described as 'The campaign ID'. The description adds no further semantic detail about the parameter beyond what the schema provides, so it scores at the baseline of 3.
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 gets scouting info for a campaign, specifying exactly what that info includes: existing lead count and instructions for triggering new scouts. This distinguishes it from sibling tools like get_b2b_stats or list_b2b_campaigns which serve different purposes.
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 explicitly says 'Use it before kicking off a scouting run,' providing clear guidance on when to invoke this tool. It also labels the tool as 'Read-only and free,' which prevents misuse. However, it does not mention alternatives or when not to use it, keeping it from a top score.
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.
