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Glama

Crc

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

A4.6/5.0
Behavior5/5

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

Annotations already declare read-only, open-world, idempotent, non-destructive. Description adds behavioral details: partial failures degrade gracefully, bundlephobia timing (5-30s on first measurement), sources_failed list, and return format. 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?

Description is a single dense paragraph that front-loads the core purpose and then details sub-checks, timing, and fallbacks. Somewhat verbose but efficient, with no wasted sentences.

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?

With no output schema, the description thoroughly explains the return structure (summary block, advisory details, links, alternative versions) and error handling. Covers all necessary context for a composite tool with two parameters.

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 description coverage is 100% (both parameters have descriptions). The tool description adds minor value (e.g., scoped packages accepted for 'package'), but largely repeats schema info (default version behavior). Limited additional meaning 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?

The description clearly states it is a composite check for evaluating whether to add an npm package, listing specific checks (license, advisories, bundle size, etc.) and explicitly noting it is npm-only in v1, distinguishing it from sibling tools like deps.dev:version.

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 says when to use (agent asks about safety/popularity/size) and when not to (PyPI/Maven/Cargo/Go use deps.dev:version directly). Provides clear usage context.

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

All Crc toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in the prediction market domain (e.g., bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk) and data querying (ask_pipeworx, ask_pipeworx_grounded, deep_research). This overlap creates confusion for an agent selecting the right tool.

Naming Consistency2/5

Naming is inconsistent: most tools use snake_case but some start with a verb (ask_, bet_, compare_) while others start with a noun (entity_profile, pipeworx_feedback, polymarket_*). There is no uniform pattern, making it harder to predict tool names.

Tool Count2/5

With 32 tools, the server is overstuffed for a single focus. It bundles checksums, AI visibility, data queries, prediction market analysis, subscriptions, memory, and more, which would be better split into separate, more focused servers.

Completeness2/5

Despite the large tool count, the server lacks completeness in key areas: no tool to place prediction market trades, no direct SEC filing detail extraction (only through generic queries), and only two checksum tools despite the server name 'Crc'. The surface feels scattershot rather than comprehensive.

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