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Gemini Crypto

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
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, which cover safety. The description adds fetching and extraction details but does not contradict annotations, so a baseline of 3 is appropriate.

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 two sentences plus a bulleted list, is front-loaded with the core purpose, and every sentence adds value with no redundancy.

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?

Although there is no output schema, the description explains the output format as a single text blob in standard markdown, which is sufficient for this simple tool. Error handling or rate limits are not mentioned but not critical.

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 description coverage is 100%, and the description adds value by specifying default and max for max_links, and explaining the extraction process, providing context 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 verb 'generate' and resource 'llms.txt file for any URL', and explains the output format and use case, distinguishing it from siblings like scan_competitor_ai_presence and ai_visibility_check.

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 (client indexing, own project, competitor audit) but does not explicitly state when not to use it or compare with alternatives, though the context is clear.

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
Disambiguation3/5

Many tools serve overlapping research purposes (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim, entity_profile, compare_entities), which could confuse an agent. However, descriptions help differentiate them by use case (single vs multi-part, grounded vs standard, etc.). Some overlap remains.

Naming Consistency3/5

Tool names mix patterns: some are verb_noun (ask_pipeworx, bet_research), others are noun_phrase (price_feed, recent_alerts) or adjective_noun (ticker_v2). No strong naming convention, but all use snake_case consistently, making them readable.

Tool Count3/5

40 tools is on the high side for a single server, covering both Gemini exchange data and Pipeworx's broad knowledge tools. While each tool serves a purpose, the scope feels broad, and some tools could be separated into dedicated servers.

Completeness4/5

The Gemini exchange tools cover essential read-only data (order book, candles, ticker, trades), but lack order placement, likely intentionally. The Pipeworx tools provide extensive research capabilities across many domains, leaving few gaps for the stated purposes.

Resources