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Seo Backlinks

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

A4.3/5.0
Behavior4/5

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

Annotations indicate the tool is read-only, idempotent, and non-destructive. The description adds behavioral details: it fetches the page, extracts title/description/key links, and emits standard markdown format. It also notes the output is a single text blob, which goes beyond annotations.

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 concise with no wasted words. The main purpose is front-loaded, process details follow, and use cases are listed efficiently. Every sentence 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 no output schema, the description explains the output format (standard markdown, single text blob) and what it extracts. For a simple two-parameter tool, this is complete enough for an agent to understand the result.

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%, so baseline 3. The description does not add additional parameter details beyond the schema descriptions. The implicit use of 'url' and 'max_links' is covered by 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 generates a production-ready llms.txt file, specifying the verb 'Generate' and the resource 'llms.txt'. It distinguishes itself from siblings like ai_visibility_check by focusing on file generation rather than visibility checks.

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 lists three specific use cases (client indexing, drafting for own project, auditing competitor) which guide when to use the tool. It does not explicitly mention alternatives or when not to use, but the examples provide adequate context.

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

A3.6/5.0
Disambiguation2/5

ask_pipeworx_beta explicitly states it currently behaves identically to ask_pipeworx, making them practically indistinguishable, and ask_pipeworx_grounded is the same router with one extra verification step. The five polymarket_* tools also share overlapping 'find/validate edge' territory, and scan_competitor_ai_presence is a direct wrapper over ai_visibility_check, so an agent must read carefully to pick correctly.

Naming Consistency3/5

Prefix families (ask_pipeworx_*, polymarket_*, seo_backlinks_*, pipeworx_*) provide some predictability, and several tools follow verb_noun (compare_entities, resolve_entity, validate_claim). However, conventions mix single verbs (remember, forget, recall), noun phrases (entity_profile, recent_changes), and seo_referring_domains breaks the seo_backlinks_* family pattern, so the overall scheme is readable but inconsistent.

Tool Count2/5

36 tools is over the 25+ 'too many' threshold even for a broad platform, and the mismatch is far worse given the server is named 'Seo Backlinks' — only 5 of 36 tools actually serve that purpose. The other 31 tools (Pipeworx research, Polymarket betting, memory, subscriptions) belong to a different scope entirely, making the set feel bloated and mislabeled.

Completeness3/5

The five genuine backlink tools cover a single-domain audit well (summary, list, anchors, referring domains, history), but they lack standard SEO workflows like multi-domain or competitor backlink comparison, and there is no tool connecting backlink data to the AI-visibility audit tools. The surrounding Pipeworx surface is extensive, but it belongs to a different domain than the server's stated purpose.

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