Check whether a package is in quantakrypto's known quantum-vulnerable dependency database (the classical crypto it exposes). Provide 'name' and optional 'ecosystem' (default npm).
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Package name to look up (e.g. 'node-forge', 'jsonwebtoken'). | |
| ecosystem | No | Package ecosystem. Default: npm. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It correctly implies a read-only lookup ('Check whether') and adds context about the database's purpose. However, it does not describe output format, error behavior, or any side effects, leaving some behavioral aspects undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main purpose, and includes essential usage details without any filler. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two parameters and no output schema, but the description does not explain what the response contains (e.g., a simple boolean versus a detailed match with crypto information). Given the parenthetical about 'classical crypto', more detail would help the agent anticipate the result; still, the core purpose is clear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers both parameters, but the description adds a meaningful default for 'ecosystem' (npm) and clarifies which parameter is required. This goes beyond the schema's descriptions and helps the agent invoke the tool correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Check whether') and the exact resource ('quantakrypto's known quantum-vulnerable dependency database'). It also specifies the input fields, making its purpose unmistakable and distinct from sibling tools that handle remediation or verification.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it (when you need to check a package against the database) and explains how to provide parameters. However, it does not explicitly mention when not to use it or provide alternative tool names for related tasks, so the usage guidance is only implied rather than explicitly contrasted.
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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Most tools have clear and distinct purposes, but there is some overlap in the fix/verify area: apply_verified_patch, verify_fix, and remediate_findings all involve verification, which could cause an agent to hesitate on which to use. However, the descriptions differentiate them well (single-fix verification vs. snippet verification vs. batch remediation). Triage and apply_triage are clearly sequential.
All tool names follow a consistent verb_noun pattern in lower_snake_case (e.g., check_dependency, list_rules, suggest_hybrid). The only slight variation is apply_verified_patch with an adjective, but it still follows verb_noun structure and the pattern is otherwise uniform.
11 tools is well within the ideal 3-15 range and each serves a distinct function in the post-quantum analysis and remediation workflow: detection, explanation, triage, remediation, and scoring. No obvious redundant tools. The count feels well-scoped for the domain.
The tool set covers analysis (explain_finding, get_fix_examples), triage (triage_findings, apply_triage), remediation (remediate_findings, apply_verified_patch), and scoring (score_delta), but there is no scan tool. All triage/remediation tools require 'findings' arrays from an external scan_path command, which is not exposed as a tool in this server. This creates a significant gap in the workflow, as agents cannot initiate scans without an external dependency.