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Energy Charts

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).

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. The description adds behavioral details: it fetches the page, extracts specific elements, and emits standard format. No contradictions.

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?

The description is a single, efficient paragraph: states purpose, process, output, and use cases. No superfluous sentences. Front-loaded with the action.

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?

The description covers purpose, process, output, and use cases. No output schema, but the description explains the output is a text blob. It is sufficient for an agent to understand and invoke the tool correctly.

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?

Input schema has 100% description coverage, so the schema already documents both parameters (url and max_links). The description mentions the parameters in passing but adds no new semantic information beyond the 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?

The description clearly states the tool's purpose: generate an llms.txt file for a URL to aid AI crawlers. It explains the process (fetches page, extracts title/description/links) and output format. The tool is distinctive from its siblings, which are unrelated (e.g., search, AI visibility).

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 provides explicit use cases: getting a client's site indexed, drafting for own project, auditing competitors. It does not specify when not to use, but the context is clear enough for an agent to decide.

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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