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Adzuna

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.

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly, openWorld, idempotent, non-destructive. The description adds critical behavioral details: partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, and sources_failed lists timeouts. This exceeds what annotations provide and helps the agent anticipate behavior.

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 fairly long but every sentence adds value. It front-loads the main purpose and then provides details on return data and edge cases. A slight trim could improve conciseness, but it remains well-structured and informative.

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 fully covers what is returned: a summary block, per-advisory details, links, and alternative versions. It also addresses error handling and partial failures. Given the tool's complexity and two parameters, this is completely adequate.

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%, so the schema already documents both parameters clearly. The description adds value by explaining that package accepts scoped names and that version defaults to latest. This is a moderate addition over the schema, justifying a 4.

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 adding an npm package, covering license, advisories, version history, bundle size, and more. It distinguishes itself from sibling tools by focusing on npm dependencies, and the verb 'scan' combined with the domain makes the purpose unmistakable.

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?

The description explicitly tells when to use the tool: whenever an agent asks about safety, popularity, size, or cost of an npm package. It also clarifies the ecosystem scope (NPM only in v1) and mentions alternative sources for other ecosystems, providing clear guidance vs. siblings.

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

All Adzuna toolsInspect
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TDQS

A3.7/5.0
Disambiguation3/5

Most tools are clearly distinct, but ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded and deep_research overlap with the base router, and the polymarket_* family contains several scanning/arbitrage tools with fuzzy boundaries. The long descriptions help, but an agent could easily call the wrong variant.

Naming Consistency3/5

There are coherent clusters (pipeworx_*, polymarket_*, ask_pipeworx_*, bare Adzuna verbs), but the overall server mixes snake_case, bare nouns, compound names, and -_prefixed names without a unifying convention. Some tools like compare_entities, entity_profile, and scan_dependency follow a descriptive style that does not match the verb_ noun pattern used elsewhere.

Tool Count2/5

37 tools is well above the 25-tool threshold, and the server named 'Adzuna' includes far more than job-search functionality: prediction markets, memory, subscriptions, npm dependency checks, AI visibility probes, and llms.txt generation. The count feels like a bundled mega-platform rather than a focused job-data server.

Completeness3/5

For a job-search-focused server, the Adzuna tools cover search, categories, history, regional stats, salary histograms, and top companies, but there is no direct job-detail or application workflow. For the broader Pipeworx research surface, coverage is very thorough, so the main completeness problem is the lack of a clear unified domain rather than a specific missing operation.

Resources