documentDocument by name (e.g. "rfc9000", "draft-ietf-quic-transport").
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| results | No | Array of matching documents |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds context about the expected name format (RFC or IETF draft), but does not describe behavior like error handling or response size. Given the annotations, this is adequate but not rich.
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 a single sentence with inline examples. It is front-loaded with the core action and the examples are directly relevant. 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?
For a simple lookup tool with one parameter, rich annotations, and an output schema, the description is mostly complete. It defines the input format and the behavior is implicitly read-only. The main gap is not explaining the difference from sibling lookup tools, but that is a usage guideline issue rather than a completeness issue.
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 schema has 0% description coverage for the 'name' parameter, so the description must compensate. It provides concrete examples ('rfc9000', 'draft-ietf-quic-transport'), which give useful format context. It doesn't define a complete pattern, but the examples are sufficient for a single string parameter.
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 says 'Document by name' with examples, but the verb 'Document' is ambiguous—it could mean 'to document' or 'get the document'. The examples clarify it's a lookup, but it doesn't explicitly state the action (e.g., 'retrieve', 'fetch'). It does distinguish from 'documents_search' by implying a direct name-based lookup.
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?
No guidance is provided on when to use this tool versus alternatives like 'documents_search', 'rfc', or 'wg'. The description only states what it does, not when to choose it over other tools.
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.
Several tools have overlapping or poorly distinguished purposes. For instance, `ask_pipeworx` and `ask_pipeworx_beta` have nearly identical descriptions, and `ask_pipeworx_grounded` also shares the same routing but adds a different output format. The `ai_visibility_check` and `scan_competitor_ai_presence` tools also overlap significantly.
There is some consistency with verb_noun patterns (e.g., `resolve_entity`, `search_within`, `subscribe`, `unsubscribe`). However, there are many deviations: `ask_pipeworx`, `pipeworx_feedback`, `pipeworx_trending`, `entity_profile`, `scan_dependency`, and `polymarket_edges` break the pattern, mixing descriptive names with non-standard prefixes.
37 tools is slightly above the ideal range for a single MCP server, but the tools cover a very broad and varied domain (IETF data, company research, prediction markets, package scanning, memory, etc.). The count is high but still within a manageable scope for a multi-purpose utility server.
The server combines tools from two very different domains: IETF Datatracker (document/WG/person lookups) and Pipeworx (data retrieval, prediction markets, company analysis). The IETF-related tools are sparse and incomplete (only document search, document, person, wg, wgs_search, rfc are present—no ability to create or modify records). The Pipeworx side is extensive but leaves notable gaps (e.g., no tool for submitting comments or editing IETF documents).