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Glama

Packagephobia

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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already cover safety; description adds details on data source (CF analytics-engine), privacy (no PII), output structure ((pack, tool, count)), and caching (5min-1h).

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 5-sentence description that is front-loaded with return type and includes all essential info without redundancy.

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?

Given a single optional parameter and no output schema, the description fully explains purpose, usage context, data provenance, and caching behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with enum description; description adds context that shorter windows surface current hotness while longer windows show steady-state demand, enhancing parameter understanding.

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 it returns top tools, packs, and call volume over a recent window, distinguishing from sibling tools focused on queries or research.

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?

Lists three specific use cases (discovering hot data, confirming canonical tool, alignment) but does not explicitly state when not to use or list alternatives.

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

A3.8/5.0
Disambiguation2/5

Several near-overlapping query tools exist: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route to the same underlying catalog, and ask_pipeworx_beta is currently described as identical to ask_pipeworx. The Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker) also heavily overlap and rely on lengthy descriptions to keep them apart.

Naming Consistency3/5

The set is uniformly snake_case and generally readable, but conventions are mixed: verb_noun (resolve_entity, suggest_questions), noun_verb (bet_research, ai_visibility_check), noun_adj (pipeworx_trending, recent_changes), and bare verbs (size, forget, recall) all appear. Variant suffixes like ask_pipeworx_beta and ask_pipeworx_grounded add further unpredictability.

Tool Count2/5

32 tools exceeds the 'too many' threshold and spans unrelated domains: package size, general data research, prediction markets, memory, and subscription management. The set would feel more coherent at roughly half the count, with several query and Polymarket tools consolidated.

Completeness3/5

For the dominant data-research purpose, the surface is reasonably complete: querying, grounded verification, deep research, entity resolution, entity profiles, comparisons, claim validation, and discovery are all covered. However, the server's stated identity ('Packagephobia') is nearly absent—only `size` and `scan_dependency` address package sizing—so the namesake domain is thin while unrelated domains are overbuilt.

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