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Glama

Alpaca

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?

The description goes beyond annotations (readOnlyHint, idempotentHint) by detailing partial failures, the 5-30s delay for bundlephobia first measurement, and the graceful degradation with a sources_failed field. It also lists exact return fields, providing comprehensive behavioral context.

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 well-structured and front-loaded with the core purpose. While comprehensive, it is slightly verbose but each sentence adds value. A minor trim could improve conciseness, but it remains efficient for the complexity.

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 thoroughly explains the return structure (summary block, advisories, links, alternative versions) and handles edge cases (partial failures, timeouts). It is fully complete for the tool's complexity.

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 coverage is 100%, so the schema already documents both parameters. The description notes version defaults to latest and that scoped packages work, but adds little beyond the schema. Baseline 3 is appropriate.

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: a composite check for evaluating npm packages, combining data from deps.dev and bundlephobia. It specifies the verb ('check'), resource ('npm package'), and scope, distinguishing it from siblings like scan_competitor_ai_presence.

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 notes the NPM-only limitation and directs users to deps.dev for other ecosystems, effectively defining when not to use it.

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

All Alpaca toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Several tools occupy heavily overlapping territory: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, six Polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread, bet_research) circle the same opportunity-finding domain, and entity_profile/recent_changes/compare_entities/validate_claim are all company-research flavored. While each pair has a stated distinction, an agent would frequently need to read deep into long descriptions to avoid misselection.

Naming Consistency3/5

All names use snake_case, so there is no style chaos, but the pattern is inconsistent: some tools are verb-first (remember, validate_claim, resolve_entity), some are noun-first (entity_profile, recent_changes, alpaca_snapshot), and many use domain prefixes (ask_pipeworx*, polymarket_*, pipeworx_*) that overlap with bare verb-noun tools. The mix is readable but does not give a predictable clue to what a tool does.

Tool Count2/5

34 tools is well above the 25+ threshold, and the count is inflated by redundant/overlapping surfaces: a beta duplicate, six overlapping Polymarket tools, and multiple meta/discovery tools (discover_tools, suggest_questions, pipeworx_trending). Only three tools actually relate to the server's stated Alpaca identity, making the scope feel sprawling rather than well-scoped.

Completeness3/5

The research/query surface is broad and covers a lot of workflows (single lookups, grounded verification, deep research, entity profiles, comparisons, change feeds). But there are notable gaps: pipeworx:// citation URIs are promised as resolvable yet no read/fetch tool exists, subscriptions cannot be updated (only created/cancelled), and the Alpaca tools are read-only with no account/order surface despite the server name. These are workaround-able but would cause friction or dead ends.

Resources