Skip to main content
Glama

Person

person
Read-onlyIdempotent

Fetch an IETF Datatracker person record by numeric ID; returns name, email addresses, and affiliated organizations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoPerson datatracker ID
urlNoPerson's URL
nameNoPerson's name
emailNoPerson's email address
photoNoPerson's photo URL
email_hashNoMD5 hash of email

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so safety is covered. The description adds value by disclosing the return fields (name, email addresses, affiliated organizations) and specifying the source domain (IETF Datatracker), which is beyond the structured metadata. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that efficiently conveys the action, resource, parameter, and return payload. Every word contributes value, with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter fetch tool with a rich annotation set and an output schema, the description covers all necessary context: what it fetches, how (by numeric ID), and what it returns. No additional behavioral or procedural details are needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema coverage at 0%, the description must clarify parameter meaning. It does so by saying 'by numeric ID', which explains that the 'id' parameter is a numeric IETF Datatracker identifier, not an arbitrary number. This adds meaningful context beyond the schema's bare 'type: number'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifically states 'Fetch an IETF Datatracker person record by numeric ID', using a clear verb and resource, and distinguishes itself from sibling tools like rfc, wg, and document by targeting person records. It also specifies the return content (name, email addresses, affiliated organizations), making the purpose fully unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context: use this when you have a numeric IETF Datatracker person ID. However, it does not explicitly mention alternatives or when not to use it, especially relative to similar-looking siblings such as entity_profile or resolve_entity. The context is clear but lacks explicit exclusions or alternative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.4/5.0
Disambiguation2/5

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.

Naming Consistency3/5

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.

Tool Count4/5

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.

Completeness2/5

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).