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Glama

Cricket

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

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds critical behavioral context: partial failures degrade gracefully, first measurement can take 5-30s, and sources_failed will list failures. This enriches the agent's understanding 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.

Conciseness4/5

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

The description is a single paragraph that front-loads the core purpose. It is packed with information but could benefit from structural elements like bullet points for the return fields. However, it remains relatively concise and effective.

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 no output schema, the description thoroughly explains the return value: a summary block with specific fields, per-advisory detail, links, and recent alternative versions. It also covers edge cases (partial failures, timing). This is complete for an agent to understand the tool's output.

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%, but the description adds value by noting that scoped packages (e.g., '@types/node') are accepted and that version defaults to latest when omitted. These details are not in the schema descriptions and help agents use parameters correctly.

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 the tool's purpose as a composite check for npm packages, combining deps.dev and bundlephobia data. It specifies the verb 'scan', the resource 'npm package', and distinguishes from siblings by being the only dependency scanning tool among the list.

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?

Explicit usage guidance is provided: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also clarifies scope limitations ('NPM ecosystem only in v1') and directs agents to deps.dev:version for other ecosystems, thus preventing misuse.

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

A3.6/5.0
Disambiguation2/5

The set mixes several near-overlapping tools: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, current_matches and match_scores largely duplicate each other, and the Polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk) has fuzzy boundaries. Long descriptions help, but an agent would often need to read deeply to pick the right tool.

Naming Consistency3/5

Most names are lowercase snake_case, but conventions vary: some are verb_noun (ask_pipeworx, scan_dependency, compare_entities), some are noun phrases (current_matches, match_info, entity_profile), and there are mixed prefixes (pipeworx_*, polymarket_*, plain names). It is readable but not a coherent naming system.

Tool Count2/5

35 tools is heavy, and only four of them (current_matches, match_info, match_scores, search_players) relate to the server's apparent cricket purpose. The rest are a sprawling general-purpose data/research/prediction-market/utility toolkit, making the surface feel bloated and off-scope.

Completeness2/5

As a cricket server, the surface is shallow: it has live matches, scores, match info, and player search, but no player stats, batting/bowling figures, team profiles, series/schedules, or historical match data. The many unrelated tools do not fill these obvious cricket-domain gaps.

Resources