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Glama

Octopus Energy

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. First observed

TDQS

A4.8/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, idempotentHint, destructiveHint. Description adds operational context: sources used (SEC EDGAR, GDELT/GNews, USPTO), USPTO sunset date and soft-fail behavior, return structure (grouped changes, total_changes, citation URIs). Good but not perfect because annotations already cover safety.

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 with all essential info front-loaded. Includes example queries, tool function, source details, parameter hints, and sibling differentiation. No superfluous sentences.

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, describes return structure. Covers error handling (soft-fail for USPTO), fallback mechanism, and parameter specifics. Comprehensive for a read-only aggregation tool with 3 params and many siblings.

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 description coverage is 100% (all three parameters described). Description adds more: 'since' accepts ISO date or relative shorthand with examples, 'value' can be ticker or CIK, 'type' only supports 'company'. Provides 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?

Description clearly states tool provides a 'change feed for a company' with specific examples like 'What's new with X' and 'latest on Y'. It explicitly distinguishes from sibling 'entity_profile' by stating when to use that instead.

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 examples, explains fallback logic (GDELT→GNews), and gives parameter guidance like 'Use "30d" or "1m" for typical monitoring'. Directly tells when to use alternative tool 'entity_profile'.

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

All Octopus Energy toolsInspect
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TDQS

A3.8/5.0
Disambiguation4/5

Most tools have clearly distinct purposes due to detailed descriptions and specific domains. However, there is potential for confusion between `ask_pipeworx` and `ask_pipeworx_grounded` (both route to data), and among the four polymarket tools, which could cause misselection if not read carefully.

Naming Consistency2/5

Naming is inconsistent: while all use snake_case, they mix verbs (`ask_`, `list_`, `bet_`, `scan_`), noun phrases (`entity_profile`, `product_details`, `recent_alerts`), and imperative verbs (`forget`, `remember`, `recall`). No single pattern is followed throughout, making it harder to predict tool names.

Tool Count3/5

With 31 tools, the server covers multiple domains (energy, general data, betting, memory, subscriptions) which feels heavy for a single server named 'Octopus Energy'. While each tool has a role, the scope is overly broad, and many tools are tangential to energy, suggesting the number could be reduced or better scoped.

Completeness3/5

For the energy domain, tools are present but only cover listing products and tariffs, missing account management or switching. For the broader domains (data, prediction markets), coverage is decent but lacks some expected features like browsing all available data sources or user profile management. The set is not fully comprehensive for any single purpose.

Resources