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Glama

Crypto Fng

by io.github.pipeworx-io

Scan Dependency

scan_dependency
Read-onlyIdempotent

Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesnpm package name. Scoped packages (e.g. "@types/node") are accepted.
versionNoSpecific version to check (e.g., "18.3.1"). Defaults to the latest published version when omitted.

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already indicate readOnly, openWorld, idempotent, non-destructive. The description adds significant behavioral context: partial failure handling, bundlephobia measurement delay (5-30s), and sources_failed reporting. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is thorough and front-loaded with purpose and usage. It is slightly dense but each sentence adds value. Minor trimming could improve readability, but overall efficient.

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 lacking an output schema, the description fully explains the return structure (summary block fields, advisory details, links, alternative versions) and handles complexities like partial failures and timeouts, making it complete for effective use.

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 descriptions for both parameters. The description adds practical usage details: acceptance of scoped packages and defaulting version to latest, enhancing understanding 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 defines the tool as a composite check for npm packages, covering license, advisories, version history, bundle size, dependency count, and ESM/tree-shake support. It distinguishes itself from siblings by explicitly noting npm-only scope and directing other ecosystems to alternative tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: 'Use whenever an agent asks 'is X safe / popular / small' or 'what does adding lodash cost me''. Also provides guidance on partial failures, timeouts, and fallback for other ecosystems.

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

All Crypto Fng toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Several tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route questions through the same underlying catalog with only subtle differences. The polymarket family (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread, bet_research) also has fuzzy boundaries. Only the Crypto Fear & Greed tools are clearly distinct.

Naming Consistency3/5

Most tools follow a snake_case verb_noun pattern, but there are notable deviations: the ask_pipeworx_* family uses object-style names, pipeworx_feedback and polymarket_edges are noun_noun, and current_index vs index_history uses 'index' inconsistently. The polymarket_* family mixes verb and noun styles internally.

Tool Count2/5

33 tools is heavy for a server ostensibly named 'Crypto Fng' — only 2 of the tools relate to that core purpose. The rest constitute a broad generic data-research and prediction-market platform that would be more appropriately scoped as its own server. The count exceeds the comfortable range for an agent to reason over.

Completeness4/5

Within the actual (broad) domain, the surface is fairly complete: discovery (discover_tools, suggest_questions), querying (ask_pipeworx family), grounded verification (validate_claim, ask_pipeworx_grounded), deep research, entity resolution/profile/comparison, memory lifecycle, and subscription lifecycle. The named crypto-sentiment domain is fully covered with current and historical index tools, though the underlying 5,708 pack tools are only reachable indirectly through the router.

Resources