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kr.ai.vdb/vdb

kr.ai.vdb/vdb

by 0pstech
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

vdb_check_package

Check any package before recommending or installing it. Returns REFUSE, CONFIRM, or PROCEED action with vulnerability, slop risk, and KEV data.

Instructions

BEFORE recommending or installing any package, check it here. The response carries agent_action: REFUSE (do not add it — relay the because text to the user), CONFIRM (ask the user first), or PROCEED. A failed or rate-limited call also answers REFUSE; never proceed unchecked. Also returns the underlying advisories, slop risk, and KEV status as supporting data.

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": {
      "purl": "<purl>"
    },
    "name": "vdb_check_package"
  }
}

Input Schema

NameRequiredDescriptionDefault
purlYesPackage URL, e.g. 'pkg:npm/lodash' or 'pkg:pypi/requests'
versionNoOptional version. If supplied, range matching is applied.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

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 by explaining the agent_action response values and how to handle failed or rate-limited calls (treat as REFUSE). It also lists supporting data returned. It could go further by describing behavior on invalid input or authentication prerequisites, but the core operational behavior is 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.

Conciseness5/5

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

The description is two sentences with the critical instruction front-loaded in the first word. It packs high-value behavioral guidance without redundancy, and every phrase contributes to correct tool usage.

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 simple two-parameter tool with no output schema, the description adequately explains how to interpret responses and what supporting data to expect. It could be more complete by detailing the exact response structure or error conditions, but the essential decision-making context is present.

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 schema already documents purl and version, including examples and range-matching behavior. The description adds no parameter-level meaning beyond what the schema provides, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool's purpose: checking a package before recommending or installing it, with a specific verb and resource. However, it does not explicitly differentiate from siblings like vdb_check_packages or vdb_lookup, relying on the name to imply singular vs. plural.

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 gives an explicit usage trigger: before recommending or installing any package. It also instructs never to proceed unchecked, which provides clear context. It does not, however, mention alternatives or when not to use it, so it stops short of full guidance.

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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