Overview of the Pinnacle Ask knowledge layer: featured content, corpus statistics, and entry points. Takes no arguments. Good first call to orient before searching.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | Sanitised jsonb projection from the locked ask_* RPC layer. | |
| tool | Yes | ||
| source | Yes | ||
| disclaimer | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds that it returns structured overview data but doesn't disclose further behavioral details beyond what annotations provide.
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 concise sentences, front-loaded with purpose, zero 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 zero-parameter input, annotations, and output schema, the description fully captures the tool's role as an orientation endpoint.
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?
No parameters in schema, and description confirms 'Takes no arguments'. Schema coverage is 100%, so no additional parameter info needed.
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?
Clearly states it provides an overview of the knowledge layer with specific content types (featured content, corpus statistics, entry points). Distinct from sibling tools like search or browse.
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 says it's a good first call before searching, providing clear usage context. No exclusions or alternatives mentioned, but the guidance is sufficient.
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 clearly distinct purpose: browse discovers taxonomy values, topic retrieves content for a value, compare does side-by-side analysis, fetch gets full answers, etc. No two tools overlap in functionality, and descriptions make their unique roles evident.
All tool names are lowercase, using underscores for compound names (lookup_code, red_flags) while others are single words. This pattern is consistent and predictable, with no mixing of conventions like camelCase.
With 11 tools covering search, retrieval, browsing, comparison, milestones, pathways, red flags, clinical code lookup, and a home overview, the count is well-scoped for a knowledge corpus. Each tool serves a necessary function without redundancy.
The tool surface covers the full user journey: orienting (home), discovering (browse), searching (search), retrieving (fetch), comparing (compare), exploring (topic, milestones, pathway, red_flags, related), and code-based lookup (lookup_code). No critical missing operations.
