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emojihub

by io.github.pipeworx-io

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
Behavior5/5

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

Annotations already declare read-only/idempotent/non-destructive. The description adds meaningful details: self-aggregating signal, CF analytics-engine source, no PII, output shape, and caching window (5min-1h). This goes well beyond the 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?

Each sentence earns its place: what it returns, when to use it, and behavioral details. The numbered use cases improve scannability without unnecessary 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?

Despite no output schema, the description compensates by naming the return contents (top tools, packs, call volume). It covers data source, caching, privacy, and usage intent, making the tool fully specified.

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 has 100% coverage for the window parameter, including enum values and semantic descriptions. The tool description merely restates the window options without adding new meaning, so it meets the baseline but adds little.

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?

Clearly states the tool returns top tools, packs, and call volume from Pipeworx. The verb 'Returns' plus resource and scope makes it distinct from sibling discovery tools by focusing on aggregate trending data.

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 three explicit use cases (discovering hot data sources, confirming canonical tool choice, aligning with agent needs). Doesn't explicitly mention alternatives, but the use cases give strong contextual guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All emojihub toolsInspect
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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there is some overlap among the numerous Pipeworx query and prediction market tools (e.g., polymarket_arbitrage vs. polymarket_edges vs. polymarket_fill_risk). Descriptions help differentiate them, so the ambiguity is minor.

Naming Consistency3/5

Tool names use a mix of verb_noun patterns (e.g., list_subscriptions, validate_claim), phrases (ask_pipeworx, bet_research), and standalone nouns (pipeworx_feedback). While readable, the lack of a single consistent convention makes the set feel less cohesive.

Tool Count3/5

33 tools is on the high side, with many highly specialized prediction market and Pipeworx management tools. The server's name 'emojihub' suggests a narrow focus, but the actual scope is much broader, making the count feel somewhat inflated for its apparent purpose.

Completeness4/5

The tool set covers a vast domain: factual data retrieval, company profiles, comparisons, claim validation, prediction market analysis, memory, subscriptions, and emoji lookup. Minor gaps exist (e.g., no direct tool for simple web search), but overall coverage is comprehensive.

Resources