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Glama

Energy Charts

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
Behavior4/5

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

Annotations already indicate readOnly, idempotent, non-destructive. Description adds valuable behavioral details: fans out to multiple sources, fallback from GDELT to GNews, USPTO soft-fail pending API sunset, and output structure. Could mention rate limits but not necessary given readOnly.

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?

Single paragraph efficiently packs user intent, data sources, input format, output structure, and sibling differentiation without wasted words. Front-loaded with relatable examples.

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?

Despite no output schema, description sufficiently explains return format (grouped changes, total count, citation URIs). Covers input format, data sources, fallback behavior, and directs to entity_profile for static needs. Complete for moderate complexity.

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

Parameters5/5

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

Schema coverage is 100%, and description adds contextual examples for each parameter (since formats, value as ticker or CIK, type limited to company). Exceeds baseline expectation.

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 begins with user query examples, then clearly states the tool's purpose as a change feed for a company in a time window, listing specific sources (SEC, GDELT/GNews, USPTO) and distinguishing from sibling entity_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 says when to use this tool ("what's new" queries) and when to use entity_profile (static profile regardless of window). Also provides guidance on the since parameter format and recommendation.

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_grounded, and deep_research, which all perform similar data retrieval. The multiple Polymarket tools also overlap in focus, making it unclear which to use for a given task.

Naming Consistency2/5

Tool names are inconsistent: some use 'ask_', 'polymarket_', 'pipeworx_', while others like 'electricity_price', 'installed_power', and 'remember' follow no coherent pattern. Conventions are mixed and unpredictable.

Tool Count2/5

With 35 tools, the server is over-scoped for an 'Energy Charts' purpose. Only 5-6 tools are directly energy-related; the rest are a miscellany of data services, prediction markets, and memory functions, which is excessive and unfocused.

Completeness2/5

The server lacks essential energy analysis tools like forecast, emission factors, or capacity utilization, yet includes many unrelated tools (e.g., betting, memory). This creates significant gaps for the stated domain.

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