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Clearlydefined Harvest Status

clearlydefined_harvest_status
Read-onlyIdempotent

List which harvesting tools (ScanCode, Licensee, REUSE, FOSSology, clearlydefined) have analysed one exact component version, and at which tool versions. Use it to judge how much evidence sits behind a definition, or to explain why a definition looks thin. Keyless.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesComponent name, e.g. "express", "log4j-core", "requests".
typeYesComponent type: "npm", "maven", "pypi", "gem", "nuget", "crate", "composer", "go", "git", "deb", "pod".
providerYesWhere it was published: "npmjs", "mavencentral", "pypi", "rubygems", "nuget", "cratesio", "packagist", "golang", "github", "debian", "cocoapods".
revisionYesExact version or commit, e.g. "4.18.2", "2.17.1", or a git SHA.
namespaceNoGroup/scope/org, e.g. "org.apache.logging.log4j" for Maven or "@babel" for a scoped npm package. Omit (or pass "-") when the ecosystem has none.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the description is not required to restate those. It adds value by disclosing 'Keyless' (no authentication needed) and specifying the output (which tools and versions). It does not contradict any annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The description is three sentences with zero waste. The core action is front-loaded in the first sentence, the use cases follow, and the final 'Keyless.' is a minimal and informative note. Every sentence earns its place.

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 read-only tool with no output schema, the description adequately explains the return (list of tools and versions) and the reason to call it. It does not mention pagination or error behavior, but for a simple status query this is not a critical gap. The tool is sufficiently described for an agent to invoke it correctly.

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%, so the baseline is 3. The description does not add significant meaning to individual parameters beyond what the schema already explains, though it ties them together by stating 'one exact component version', reinforcing that revision is required. It adds no new parameter-level detail, so 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 uses a specific verb ('List') and a precise resource ('which harvesting tools have analysed one exact component version'), naming the five tools explicitly. This clearly distinguishes it from sibling tools like clearlydefined_definition (which would return the definition) and clearlydefined_search (which searches broadly). No ambiguity remains about the tool's function.

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?

The description provides explicit guidance on when to use it: 'Use it to judge how much evidence sits behind a definition, or to explain why a definition looks thin.' This establishes clear use cases. However, it does not explicitly contrast with alternatives or state when not to use it, so it stops short of a full 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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