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Glama

Newsdata

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").

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already indicate readOnly, idempotent, non-destructive. Description adds multi-source fan-out, fallback logic, soft-fail behavior, and return structure with citation URIs, all consistent 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.

Conciseness4/5

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

Description is a single paragraph but front-loaded with purpose and use cases. It's informative and avoids fluff, though could be more structured for easier parsing.

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?

Given complexity (multi-source, fallback, no output schema), description covers return format (changes grouped by source, counts, URIs) and explains when to use alternative tool. Complete for read-only monitoring tool.

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 already describes all 3 parameters clearly (100% coverage). Description goes beyond with example values, relative shorthand explanations, and typical monitoring advice ('Use 30d or 1m'), adding useful context.

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?

Description clearly states the tool provides a change feed for a company from SEC EDGAR, GDELT/GNews, and USPTO within a time window. It also distinguishes from sibling tool entity_profile which provides a static profile.

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?

Explicitly gives example queries and when to use entity_profile instead. Also explains fallback behavior (GNews when GDELT rate-limited) and soft-fail for USPTO.

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

All Newsdata toolsInspect
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TDQS

A4/5.0
Disambiguation3/5

Most tools have clearly distinct roles, and the extensive descriptions help differentiate intent, but the ask_pipeworx family—especially ask_pipeworx_beta, which is currently identical to ask_pipeworx—creates real ambiguity. Overlapping entry points like ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim could also cause misselection without careful reading.

Naming Consistency4/5

All 34 tools use consistent snake_case, and clear verb-led or noun-prefixed patterns emerge across families like ask_pipeworx*, polymarket_*, and remember/recall/forget. Minor deviations such as ai_visibility_check and recent_changes being noun phrases rather than verb_noun constructions prevent a perfect score.

Tool Count2/5

34 tools is well above the 25-tool threshold for over-scoping, making the set heavy for an agent to navigate. While the server spans many domains, several tools like generate_llms_txt, scan_dependency, and ai_visibility_check feel tangential to the core news/research purpose and would be better split into separate servers.

Completeness4/5

The core news/research domain is well covered: lookup, grounded verification, deep multi-source research, entity profiles, comparisons, subscriptions, and alert feeds are all present with no obvious dead ends. Minor gaps exist—such as no direct full-text article retrieval or a dedicated free-text news search beyond latest_news filters—but agents can work around them.

Resources