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Fivebar Trading

by io.github.fivebar-xyz
OverviewDiscussionsAdmin

Is this package safe to install?

package_check
Read-only

Before installing an npm, PyPI or crates.io package (or letting an agent install one): OSV's known vulnerabilities and malicious-package reports for that version, whether its name is one typo from a popular package with a fraction of its downloads (typosquatting), install-time scripts that run code on your machine (npm), whether the newest version was published by an account that published none before it (a hijack sign), age, downloads, deprecated or yanked, and whether it links its source. Verdict: high risk, caution or no warnings, with reasons. Use for 'is this npm package safe?', 'should I pip install X?', 'is lodahs legit?'. Facts, not an accusation of the authors.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "package_check"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesPackage name, optionally with a version (express@4.18.2) or ecosystem prefix (pypi:requests, crates:serde)
versionNoVersion to check. Default: the latest
ecosystemNoDefault npm

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

With readOnlyHint and openWorldHint already declaring the safety profile, the description adds real behavioral context: the upstream data source (OSV), the ordinal verdict scale (high risk / caution / no warnings) with reasons, and a framing note that results are 'facts, not an accusation of the authors.' It does not cover behavior for unknown or unpublished package names, which keeps it below 5.

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 content is dense and front-loaded, and nearly every clause carries a distinct check an agent would care about. The opening sentence is an unpunctuated run-on list without a governing verb, and the 'Verdict:' fragment is stylistically loose, which costs a point on structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a three-parameter read-only lookup with no output schema, the description does the needed work by enumerating the signals checked and the shape of the result (verdict plus reasons). Minor gaps remain around handling of nonexistent packages or ambiguous names, but nothing essential for correct invocation is missing.

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 name, version, and ecosystem are fully documented with format examples and defaults. The description corroborates the ecosystem scope and that checks apply 'for that version,' but adds no syntax or semantics beyond the schema, so the baseline of 3 applies.

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 names a concrete resource (an npm/PyPI/crates.io package at a specific version) and the exact evidence it aggregates: OSV advisories, malicious-package reports, typosquatting distance, install-time scripts, first-time-publisher hijack signals, age/downloads, deprecation/yank status, and source linkage. That level of specificity distinguishes it from neighboring checks like repo_check or mcp_check, which operate on different artifacts.

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

Usage Guidelines4/5

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

It states the trigger clearly ('Before installing ... or letting an agent install one') and supplies example phrasings ('is this npm package safe?', 'should I pip install X?'). There is no explicit exclusion or named alternative tool, so it falls short of a 5.

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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