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Remoteok

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?

Discloses that it 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format', adding context beyond the readOnlyHint and idempotentHint annotations. However, it does not mention potential limitations like rate limiting or page access restrictions.

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?

Three concise sentences that front-load the purpose, then detail the process and use cases, with no redundant or vague phrasing.

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?

Adequately covers the tool's behavior and output format given the simple schema and annotations. Could mention that it only works for publicly accessible pages or cite output format details, but overall sufficient.

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 description coverage is 100%, so the description adds little new meaning beyond the parameter descriptions. It mentions 'max_links' default and max, but this is already in 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 the resource 'production-ready llms.txt file', and specifies the distinct purpose of enabling AI crawlers to index a site. It differentiates from sibling tools like 'ai_visibility_check' by focusing on file generation.

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 explicit use cases (getting client's site indexed, drafting llms.txt, auditing competitor) but does not mention when to avoid this tool or suggest alternatives among siblings.

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

A3.9/5.0
Disambiguation2/5

Several tool clusters have fuzzy boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer questions through the same routing layer, while polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and bet_research all address prediction-market edges. Even with detailed descriptions, an agent can easily select the wrong variant.

Naming Consistency3/5

Names are uniformly lowercase snake_case and many follow a verb_noun pattern (list_jobs, search_jobs, resolve_entity, validate_claim), but there are numerous noun-first and adjective-first exceptions (entity_profile, recent_alerts, pipeworx_trending, polymarket_arbitrage) plus bare verbs (remember, forget, recall, subscribe). The pattern is readable but not consistently applied.

Tool Count2/5

34 tools is well above the well-scoped range, and the vast majority are not about the server's RemoteOK namesake. The set appears to merge several distinct domains (Pipeworx data research, Polymarket betting, RemoteOK jobs, memory utilities) into one oversized surface, making it feel more like a bundled platform than a focused server.

Completeness4/5

For the dominant Pipeworx/data-research theme, coverage is strong: question answering, grounded verification, entity profiles, comparisons, change feeds, discovery, memory, subscriptions, and citation-based research are all present. The RemoteOK job subset covers list/search/get without obvious dead ends. Minor gaps exist (no direct citation-URI fetcher, no job alert subscriptions), but agents can work around them.

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