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Geonet Nz

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

A4.7/5.0
Behavior5/5

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

Annotations already indicate read-only and idempotent behavior. Description adds significant context: parallel call structure, source fallback (GDELT to GNews), soft-failure for patents, return format with grouped changes and citation URIs.

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 efficient with front-loaded query examples. Every sentence adds value, though slightly longer than minimal.

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?

Covers multiple sources, fallback, return structure, and soft-failure. Lacks explicit error handling but is sufficient for a read-only tool without output schema.

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 baseline is 3. Description enriches with examples of 'since' formats, recommended default ('30d'), and explains 'value' can be ticker or CIK, and 'type' is limited to 'company'.

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 it is a change feed for a company in a time window, lists specific sources (SEC EDGAR, GDELT/GNews), and explicitly distinguishes from entity_profile for static profiles.

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?

Description provides explicit query examples and directly tells when to use entity_profile instead. It also explains fallback mechanisms for news sources, giving clear usage context.

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

A3.9/5.0
Disambiguation2/5

Several tools are deliberately near-identical variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) or have overlapping routing/query purposes (deep_research, validate_claim, discover_tools, suggest_questions). The Polymarket cluster also has five tools that all surface 'edges' or 'arbitrage' with only subtle differences. Only the three GeoNet tools and the memory trio are cleanly distinct.

Naming Consistency3/5

The dominant style is snake_case, and clusters like ask_pipeworx_* and polymarket_* are internally consistent. However, verb/noun patterns vary widely across the set: some tools begin with verbs (get_quake, scan_dependency, generate_llms_txt), some are noun phrases (entity_profile, volcano_alerts, recent_changes), and some are plain nouns (polymarket_arbitrage). Readable but not a single predictable convention.

Tool Count2/5

34 tools is well above the 'heavy' threshold, and the server is named 'Geonet Nz' while only 3 of its 34 tools relate to GeoNet. The overwhelming majority are Pipeworx/data/prediction-market tools, making the server's scope massively broader than its name implies. The count itself is not unreasonable for the actual feature sprawl, but it is inappropriate for the apparent purpose.

Completeness4/5

Taking the real scope as 'general authoritative data research + memory + subscriptions + a little GeoNet', the surface is quite complete: query entry points, grounded verification, deep research, entity resolution, comparisons, claim validation, monitoring subscriptions, memory persistence, and feedback are all present. The GeoNet-specific subset is also adequate (get one, list recent, volcano alerts). Minor gaps exist, like no general GeoNet station/well data or subscription editing, but nothing causes dead ends.

Resources