papers.listList all 197 papers in the Urantia Book with their metadata (id, title, partId, labels). Use toc.get for a hierarchical view instead.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| papers | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable context by specifying the fixed count (197), the metadata fields returned, and the fact that it returns 'all' papers, which goes beyond annotation data without contradicting it.
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 perfectly concise: two short sentences, the first stating the action and result, the second pointing to an alternative. No wasted words, and the key information is front-loaded.
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 tool is simple (no parameters), has full annotations and an output schema. The description covers the essential behavioral context: what it lists, what fields are included, and how it differs from toc.get. There is no missing information that would hinder correct selection or invocation.
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?
The tool has zero parameters, so schema coverage is 100% by default. The description adds meaning by listing the metadata fields (id, title, partId, labels) that will appear in the output, giving the agent a preview of the result structure without needing parameters.
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 lists all 197 papers in the Urantia Book with specified metadata fields (id, title, partId, labels). It uses a specific verb 'list' and explicitly distinguishes itself from toc.get, which provides a hierarchical view.
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 provides explicit guidance: 'Use toc.get for a hierarchical view instead.' This tells the agent when to use this tool (flat list) versus an alternative, effectively communicating the use case.
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 resource and action (e.g., audio.get vs bible.book vs entities.list). There is no overlap, and even similar tools like search.fulltext and search.semantic are clearly differentiated by mode.
All tools follow a consistent 'domain.action' pattern using lowercase and dots. Underscores within domain names (e.g., urantia_parallels) are uniform. No mixing of camelCase or irregular verbs.
19 tools is well-scoped for a server covering the Urantia Book and Bible integration. Each tool serves a distinct purpose without bloat or insufficiency.
The surface covers all core operations: browsing (list/get for papers, entities, paragraphs), searching (fulltext and semantic), structured navigation (toc.get, papers.sections), audio, and Bible parallels. No obvious gaps.