Skip to main content
Glama

Imei

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

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false. Description adds non-redundant context: self-aggregating from CF analytics-engine, no PII, caching behavior (5min-1h), and output structure (pack, tool, count). Adds value 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?

Description is four sentences with a bullet list. Every sentence is meaningful, no waste, front-loaded with the core behavior.

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?

For a simple read-only tool with one optional parameter and no output schema, the description fully covers purpose, usage, behavior, and parameter semantics.

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 coverage is 100% with an enum for window. Description adds guidance: 'Shorter windows surface what's hot right now; longer windows show steady-state demand.' This adds usage context beyond 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 'Returns the top tools, top packs, and total call volume' with specific verb and resource. It distinguishes from sibling tools like 'discover_tools' by focusing on trending usage rather than available tools.

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 provides three specific use cases (discovering hot data sources, confirming canonical tool, seeing alignment) but does not explicitly mention when not to use it or compare to alternatives.

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

All Imei toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Several tools have unclear boundaries: ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, and deep_research, validate_claim, discover_tools, and suggest_questions all overlap with the ask_pipeworx family. The prediction-market cluster also has six tools whose distinctions require careful reading, making mis-selection likely.

Naming Consistency3/5

Most names are lowercase snake_case and reasonably descriptive, but no consistent verb_noun pattern holds across the set. entity_profile, recent_alerts, and pipeworx_trending are noun phrases, while compare_entities, resolve_entity, and validate_imei are verbs, and the useful ask_pipeworx_* and polymarket_* prefixes are not applied server-wide.

Tool Count2/5

33 tools is too many for an agent to navigate efficiently, especially since the underlying data surface is already hidden behind ask_pipeworx and dozens more tools. The set spans data research, prediction markets, memory, subscriptions, IMEI validation, dependency scanning, and llms.txt generation, making it feel like a grab bag rather than a focused server.

Completeness3/5

The main query/verify/research/monitor workflow is covered well: ask, grounded, deep research, claim validation, entity profiles, comparisons, subscriptions, and memory all exist, so common paths have few dead ends. However, the set is not a single coherent domain, and there is no direct fetch/read-record tool or prediction-market execution tool, leaving some reasonable follow-up actions implicit.

Resources