Return your Chat Hub inbox: recent AI coach conversations and any pending messages. Use it to pick up where an earlier coaching thread left off. Read-only and free; takes no parameters beyond an optional result limit.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max conversations to return |
| 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 declares 'Read-only and free; takes no parameters beyond an optional result limit', which adds useful behavioral context beyond the annotations (which already set readOnlyHint=true). It confirms the tool does not consume credits or require parameters, though it could mention response format or pagination behavior with an output schema present.
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 extremely concise at two sentences, front-loading the core purpose and adding usage guidance without any wasted words. Every sentence serves a distinct purpose: purpose, usage, and behavioral traits.
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 optional parameter, an output schema (so return values are documented), and rich annotations (readOnlyHint, openWorldHint), the description provides complete context. It covers purpose, when to use, behavioral traits, and parameter usage. No gaps remain for this simple tool.
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 100% schema description coverage, the schema already documents the 'limit' parameter well. The description adds context by calling it an 'optional result limit', which is helpful but not essential given the schema already provides rich details (default, max, min). A slight step above baseline 3 due to clarifying it is optional.
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 'Return your Chat Hub inbox' with specific resources ('recent AI coach conversations' and 'pending messages'). This provides a specific verb+resource combination that effectively distinguishes it from sibling tools like get_tasks or get_started.
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 tells when to use this tool ('pick up where an earlier coaching thread left off') and states it is 'Read-only and free'. It implicitly warns against using it for modifying data or paid access, effectively differentiating it from write tools like create_idea or update_idea.
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.
