Return the workspace 'brain index' — every wiki page's title, slug, and one-line summary, in hierarchy order. Call this at the START of a session to learn what the workspace already knows before searching, asking the user, or creating anything. Requires an active workspace.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses the return content (every wiki page's title, slug, summary, ordered hierarchically) and a usage constraint (requires active workspace). It does not mention pagination or limits, but for a zero-parameter read tool, the transparency is adequate.
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 containing all essential information: what the tool returns, when to use it, and a prerequisite. No wasted words, front-loaded with the main 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 description is complete for a simple tool with no parameters and no output schema. It explains the return value, usage context, and condition (active workspace). Could mention if there are any limits on page count, but not essential for a get-index 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?
Tool has zero parameters, so baseline score is 4. No parameter information is needed, and the description correctly omits parameter details.
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 it returns the workspace brain index with specific fields (title, slug, one-line summary) in hierarchy order. It distinguishes itself from sibling tools like search or graph query by offering a full index of all pages, not a filtered or related query.
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 recommends calling at the start of a session to learn what the workspace knows before searching, asking, or creating. Mentions prerequisite of an active workspace, though it doesn't explicitly list when not to use or compare to alternatives.
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 has a distinct purpose covering booking, brain access, commerce quoting, and three separate discovery searches (creators, curators, podcasts). No two tools overlap in functionality, making selection unambiguous.
All tools follow the pattern 'pitchiq_v1_<category>_<action>', with consistent snake_case and clear categorization (booking, brain, commerce, discover). Actions are descriptive and uniform within categories.
Eight tools cover the server's apparent scope (booking, knowledge graph, discovery) without redundancy or omission. The count is well-scoped for the intended use cases.
While booking and discovery are reasonably complete, the brain component lacks write operations (create/update wiki pages), which limits agent ability to modify knowledge. The surface feels slightly incomplete for full workspace management.