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Octopus Energy

by io.github.pipeworx-io

Generate llms.txt

generate_llms_txt
Read-onlyIdempotent

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL of the site to summarize, e.g. "https://example.com" or a specific landing page.
max_linksNoMaximum number of link entries to include (default 25, max 50).

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, open world, non-destructive. Description adds concrete behavior: fetches page, extracts title/description/key links, emits standard markdown format. 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?

Two sentences, front-loaded with purpose, no wasted words. Structure is clear and efficient.

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 the tool's simplicity (2 params, no output schema), the description fully explains input, process, and output format. Covers all necessary context for an agent.

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

Parameters3/5

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

Schema coverage is 100% with detailed descriptions for both parameters. The description adds no additional meaning beyond what's in the schema (e.g., examples are already implied). Baseline 3 is appropriate.

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?

Clearly states the verb 'generate', the resource 'llms.txt file for any URL', and the goal of indexing for AI crawlers. Distinguishes from siblings like ai_visibility_check and scan_competitor_ai_presence which are about auditing rather than generating.

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?

Provides specific use cases: getting a client's site indexed, drafting for own project, auditing competitor. Could be improved by explicitly stating when not to use, but the examples are 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