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Seo Backlinks

Pipeworx Trending

pipeworx_trending
Read-onlyIdempotent

What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNo24h (default) | 7d | 30d. Shorter windows surface what's hot right now; longer windows show steady-state demand.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already convey read-only, idempotent, non-destructive nature. The description adds valuable behavioral context: data is self-aggregating from CF analytics-engine, no PII, and cached for 5min-1h depending on window. No contradictions with 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, front-loaded with purpose, and every sentence adds value. Use cases are bulleted logically. 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?

The tool is simple (1 optional param, no output schema). The description fully covers purpose, use cases, data source, caching, and privacy. No gaps given the complexity.

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 for the single parameter 'window'. The description adds meaning by explaining shorter vs longer window trade-offs ('shorter windows surface what's hot right now; longer windows show steady-state demand'), which goes beyond the enum labels.

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 that the tool returns top tools, top packs, and total call volume over a recent window. It uses specific verbs like 'returns' and 'calling on', and the resource (trending data) is well-defined. It distinguishes itself from siblings like 'ask_pipeworx' and 'discover_tools' by focusing on trending usage metrics.

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?

Three explicit use cases are provided: discovering hot data sources, confirming canonical choice, and seeing alignment. It also notes window behavior (shorter for hot vs longer for steady-state). However, it does not explicitly state when to avoid using this tool or mention alternatives, so it's slightly incomplete.

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.