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spacenews

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

A4.9/5.0
Behavior5/5

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

Beyond annotations (readOnly, idempotent, openWorld), the description discloses the fan-out to multiple sources, GDELT→GNews fallback on rate limits/5xx, USPTO soft-fail due to PatentsView sunset, and the parallel execution model. This is significant behavioral context not inferable from 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 dense but every sentence provides unique value: natural language triggers, source fan-out, parameter formats, return structure, and an explicit alternative. No filler; front-loaded with user intents.

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 complex tool with no output schema, the description covers the return shape (changes[], total_changes, citation URIs), the various data source behaviors, and temporal parameter handling, making it sufficiently complete for an agent to invoke correctly.

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 covers all parameters with descriptions, and the description adds valuable examples (ISO date '2026-04-01' vs relative '7d', ticker 'AAPL' vs zero-padded CIK) and clarifies the `since` semantics. It goes beyond the schema's baseline by illustrating accepted values.

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 defines the tool as a change feed for a company over a time window, with natural language intents and explicit data sources (SEC, GDELT/GNews, USPTO). It distinguishes itself from the sibling tool entity_profile by specifying when to use the alternative.

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?

Provides explicit usage context: 'What's new with X' / 'latest on Y' etc., and states when to use entity_profile instead. Also gives guidance on the `since` parameter format and fallback behavior, enabling the agent to choose correctly.

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

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TDQS

A3.6/5.0
Disambiguation3/5

Several tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research. While each has distinct nuances, they could be confused by an agent.

Naming Consistency3/5

Most tools use snake_case, but the naming pattern is inconsistent (e.g., bet_research vs. polymarket_arbitrage vs. ai_visibility_check). There is no strong verb_noun pattern across the set.

Tool Count2/5

34 tools is high given the server's stated purpose ('spacenews'). Only a few tools directly relate to space news; the bulk are general-purpose Pipeworx utilities, making the scope too broad.

Completeness2/5

For a space news server, the tool surface is incomplete: only get_articles, get_blogs, and search_articles are relevant. Missing tools for article details, source filtering, or categories. The extensive general tools don't make up for this gap.

Resources