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Mempool Space

by io.github.pipeworx-io

AI Visibility Check

ai_visibility_check
Read-onlyIdempotent

Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass _apiKey to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entityYesThe thing to ask about. Brand/business name, product name, person, or topic. E.g. "Pipeworx", "OpenInvoice", "Acme Corp pricing".
modelsNoWhich models to probe. Supported: "workers-ai" (free default), "anthropic" (requires _apiKey). Omit for just workers-ai.
_apiKeyNoOptional Anthropic API key (sk-ant-...) — only needed if "anthropic" is in models. Passed straight through to api.anthropic.com.
contextNoOptional: a phrase locating the entity (e.g. "Boston restaurant", "B2B SaaS"). Helps disambiguate common names.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only, open-world, idempotent, non-destructive. Description adds value by detailing the probe behavior, per-model return structure, and that Anthropic calls are billed to user.

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?

Concise, front-loaded with core action, every sentence adds value. No fluff.

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 format (per-model objects + combined view). Covers all key aspects for agent usage given tool 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?

All 4 parameters have schema descriptions. Description adds examples for entity, explains default model, and clarifies _apiKey usage, going beyond 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?

Description clearly states the tool probes LLMs and scores visibility, with specific verb and resource. Sibling tools are mostly unrelated (Pipeworx, Bitcoin, Polymarket), so it differentiates well.

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?

Explicit use cases: AI-marketing audits, pre-launch brand checks, competitive monitoring. Default model and BYO key explanation provide clear context, though no explicit when-not-to-use.

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

B3.1/5.0
Disambiguation2/5

The set mixes two unrelated domains — Bitcoin mempool explorer tools and the much larger Pipeworx data-query platform — and within the Pipeworx half several tools route to the same 5,743-tool catalog (ask_pipeworx, deep_research, discover_tools, suggest_questions). ask_pipeworx_beta is currently an exact behavioral duplicate of ask_pipeworx, and the polymarket_* family has fuzzy boundaries (arbitrage vs edges vs fill_risk, with fill-checking living in both polymarket_arbitrage and polymarket_fill_risk), so an agent must read long descriptions to avoid misselection.

Naming Consistency3/5

All names use snake_case and there are recognizable sub-families (get_* Bitcoin lookups, ask_pipeworx_*, polymarket_*), but conventions are mixed across the whole set: bare-noun state tools (block_height, hashrate, mempool_stats, mining_pools) sit beside verb_noun actions (get_block, list_subscriptions), and prefix placement is inconsistent (ask_pipeworx vs pipeworx_trending/pipeworx_feedback). The naming is readable but not predictable enough to guess a tool's name from its function.

Tool Count2/5

41 tools is well past the 25+ threshold for a coherent server, and the count is inflated by bundling two unrelated products under a server named after only the smaller half (~10 Bitcoin tools vs ~31 Pipeworx tools). Many Pipeworx tools are convenience wrappers around one universal router, adding surface area without adding genuinely new capabilities.

Completeness3/5

Each half is internally workable: the Bitcoin side covers blocks, transactions, addresses, fees, hashrate, and pools, while the Pipeworx side provides broad query, research, subscription, and memory lifecycles. However, there are notable gaps relative to each domain (no block-list/fee-history endpoints on the explorer side; no direct per-source CRUD on the data side), and no single coherent domain is fully served because the server's stated identity matches only a fraction of its tools.

Resources