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Seo Backlinks

by io.github.pipeworx-io

Search Within a Source

search_within
Read-onlyIdempotent

Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe document text to search inside (max ~200K chars).
limitNoMax passages to return (1-20, default 5).
queryYesNatural-language query — what passages do you want? E.g. "supply-chain risk", "fiscal year 2024 revenue", "drug interactions with warfarin".

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. Description adds technical details: BGE-base-en embeddings, 500-char overlapping windows, 200K char cap with truncation flag, and character offsets for verification. This far exceeds annotation coverage and reveals critical behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences efficiently convey purpose, usage, and technical details. Front-loaded with core purpose. Could be slightly more structured by separating usage from implementation, but no wasted words.

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?

No output schema, but description explains return values: 'top-N passages with character offsets and similarity scores.' Also covers truncation, pairing with sibling tools, and maximum input size. Fully complete for an agent to invoke correctly.

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 has 100% coverage with descriptions. Description adds value by providing examples for query (e.g., 'supply-chain risk') and clarifying constraints for text (max 200K chars) and limit (1-20, default 5). Enhances understanding beyond schema alone.

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?

Description clearly states 'semantic search INSIDE a fetched record' with a specific verb and resource. It distinguishes from siblings by contrasting with cramming text into prompts and pairing with ask_pipeworx_grounded, showing unique value.

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?

Tells when to use: 'when the record is too big to cram into the prompt — search_within saves context.' Mentions pairing with ask_pipeworx_grounded, providing context for alternative usage. No explicit when-not-to-use, but clear enough.

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.

Resources