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check_before_install

Call this before adding a dependency. Returns only the facts a reviewer would be annoyed to discover afterwards: whether the publisher has withdrawn the package, whether it runs scripts on the installing machine, whether its repository is archived, how many advisories are on record, whether the licence is source-available, and how long since it was actually published. Each fact carries the address of the body that published it. It does not say whether to install; it says what is on record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesPackage name as the registry spells it.
registryYes

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses that the tool returns only factual records, each fact carries the publisher's address, and it explicitly avoids making an install decision. It does not mention potential side effects, errors, or rate limits, but for a 'check' tool the main behavioral traits are well covered.

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 three sentences, front-loaded with the key usage instruction, and every sentence adds substantive detail (what facts, their provenance, and the tool's non-decisional nature). It is slightly dense but not verbose, and there is no filler or repetition.

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?

Given there is no output schema and no annotations, the description is remarkably complete: it enumerates the main result categories and their provenance, and explicitly states the tool's scope (record-only, no recommendation). It lacks edge-case behavior (e.g., package not found) and registry parameter details, but for a simple two-parameter tool it covers the essential context well.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema describes the 'name' parameter well ('Package name as the registry spells it') but leaves 'registry' as a bare string with no explanation. The description does not compensate for this gap; it never explains what registry values are valid, where the registry is, or how the two parameters interact. With only 50% schema coverage, the description should have added this crucial context.

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 ('check before install'), clearly identifies the resource (a dependency), and enumerates the exact facts returned (withdrawn, scripts, archived, advisories, license, publish time). It also distinguishes itself from sibling tools by stating it only reports facts and does not make an install recommendation, making 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 Guidelines4/5

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

It explicitly says 'Call this before adding a dependency', which is a clear when-to-use directive. It also explains what the tool does not do (does not say whether to install), providing an implicit exclusion. However, it does not name specific alternative tools for cases when the user wants a recommendation or deeper analysis, so it falls 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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TDQS

B3.1/5.0
Disambiguation5/5

Each tool targets a distinct query type: package status, stack review, provider incidents, model pricing, watchlist changes, etc. Even similar-sounding tools like check_package and check_stack are clearly differentiated by granularity (single package vs. whole manifest). The descriptions further remove ambiguity.

Naming Consistency3/5

All names use lowercase snake_case, but the pattern is mixed: some are imperative verb_noun (check_package, find_model, watch_add) while many are noun phrases (advisory_severity, provider_incidents, runtime_deadlines). This is readable but not a consistent verb_noun style, so there is noticeable inconsistency.

Tool Count2/5

At 31 tools, the count exceeds the 'too many' threshold (25+). While the domain is broad, the agent must navigate a large surface with many similarly scoped utilities, making selection harder. A more consolidated set (e.g., grouping related readings) would improve appropriateness.

Completeness4/5

The tool surface covers a wide range of supply-chain intelligence: package advisories, provider status, model pricing, runtime EOL, and watchlist changes. The only notable gap is lifecycle management for the private watchlist (e.g., no watch_remove or watch_list), but the overall coverage is strong.