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Glama

Rxnorm

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds value by detailing multi-source fan-out, rate-limiting fallbacks, and output structure (changes[], total_changes, citation URIs). No contradictions.

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

Conciseness4/5

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

Well-structured and front-loaded with purpose. Efficiently packed with information in a single paragraph. Could benefit from slight structural separation (e.g., parameters), but overall concise.

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

Completeness4/5

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

Given the tool's complexity (multiple sources, fallbacks, soft-failure) and absence of an output schema, the description covers essential behavioral details and output format. Limitations (USPTO) and alternatives (entity_profile) are noted.

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?

Schema coverage is 100%, so the baseline is 3. The description enriches with examples (ISO date, relative shorthand like '30d', ticker vs CIK) and usage notes (typical monitoring window). Adds meaningful context beyond schema.

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 clearly states the tool's purpose: fetching recent changes (SEC filings, news, patents) for a company in a time window. It gives example queries and explicitly distinguishes from sibling tool 'entity_profile', making the purpose unambiguous.

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

Usage Guidelines5/5

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

Excellent usage guidance: example queries, fallback behavior (GDELT preferred, GNews on rate limit/5xx), soft-fail for USPTO until May 2025, and clear directive to use 'entity_profile' for static profiles regardless of window.

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

All Rxnorm toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Several tools blur together: ask_pipeworx_beta currently duplicates ask_pipeworx exactly, ask_pipeworx/ask_pipeworx_grounded/deep_research/validate_claim all route natural-language questions to data sources, and the prediction-market tools (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, bet_research) have fuzzy boundaries. The detailed descriptions help, but an agent can easily misselect among them.

Naming Consistency3/5

All names are lowercase snake_case and the rxnorm_, polymarket_, and pipeworx_ prefixes create readable groupings, but the set mixes imperative verb-object names (validate_claim, list_subscriptions), noun-phrase names (entity_profile, recent_alerts), and bare verbs (remember, forget). It is readable but not a predictable uniform naming convention.

Tool Count2/5

35 tools is in the too-many band for a coherent server, and the Rxnorm identity makes it worse: only 4 tools are actually RxNorm-specific while 31 are unrelated Pipeworx, prediction-market, memory, and utility tools. A focused RxNorm server would need a fraction of this surface.

Completeness3/5

The four rxnorm_* tools plus resolve_entity cover the main RxNorm lookup flow (search, properties, related, NDC), so the core is not broken. But the set lacks a reverse NDC-to-concept lookup and the 31 non-RxNorm tools do not complete any single coherent domain, leaving notable gaps relative to the server's stated purpose.

Resources