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Octopus Energy

by io.github.pipeworx-io

Tariff Unit Rates

tariff_unit_rates
Read-onlyIdempotent

Time-series of electricity unit rates for a specific tariff — for Agile this is the half-hourly wholesale-tracked pricing. Returns {count, results:[{value_exc_vat, value_inc_vat, valid_from, valid_to, payment_method}]} in p/kWh, newest first. Set kind="standing_charges" for the p/day standing charge instead. Defaults to the most recent rates; pass period_from/period_to to bound a window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoWhich series to fetch. Default "standard_unit_rates".
page_sizeNoResults per page (default 100, max 1500).
period_toNoISO-8601 end, e.g. "2026-06-02T00:00Z".
tariffCodeYesTariff code from product_details, e.g. "E-1R-AGILE-24-10-01-C" (the trailing letter is the GSP region).
period_fromNoISO-8601 start, e.g. "2026-06-01T00:00Z".
productCodeYesProduct code, e.g. "AGILE-24-10-01".

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "productCode": "AGILE-24-10-01",
+    "tariffCode": "E-1R-AGILE-24-10-01-C"
+  },
+  {
+    "kind": "standing_charges",
+    "period_from": "2026-06-01T00:00Z",
+    "period_to": "2026-06-02T00:00Z",
+    "productCode": "AGILE-24-10-01",
+    "tariffCode": "E-1R-AGILE-24-10-01-C"
+  }
+]
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint true and destructiveHint false, which the description complements by stating the tool returns data (no mutations). It adds beyond annotations: specifies newest-first ordering, default to most recent rates, and output structure with fields. No contradiction.

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?

Very concise: two sentences with no fluff. First sentence states purpose and example; second sentence covers alternative usage and parameter behavior. Every phrase adds value.

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 6 parameters, 2 required, no output schema, the description fully explains the output format, default behavior, and all parameter usage. It compensates for the missing output schema by explicitly listing fields. Covers all necessary context for correct invocation.

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 description adds extra usage context: explains that for Agile it's half-hourly pricing, that kind can be 'standing_charges', and that period_from/period_to bound a window. This goes beyond the schema's 'ISO-8601 start/end' descriptions.

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 the tool returns time-series of electricity unit rates for a specific tariff, with explicit mention of Agile's half-hourly pricing. It distinguishes from standing charges by setting kind='standing_charges', and the output format is fully detailed. No other sibling tool serves the same purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains how to switch between unit rates and standing charges using the 'kind' parameter, and how to constrain the time window with period_from/period_to. It does not explicitly state when not to use it, but the sibling tools are diverse and unrelated, so guidance is sufficient.

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

A3.8/5.0
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