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

Annotations already declare readOnlyHint and idempotentHint, and the description goes well beyond them. It discloses data sources, caching, rate limit (60/minute), no auth requirement, and the exact return fields including the anomaly_score range and maintainer_health values. This gives an agent a strong, accurate model of the tool's behavior.

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 dense but mostly purposeful: purpose, data source, cache behavior, return fields, rate limit, auth, and audience are all front-loaded. The trailing report_feedback fallback is boilerplate that adds noise, but the rest is efficiently structured and each technical detail 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?

For a tool with multiple output fields, external API dependencies, and rate limiting, the description is largely complete. It covers safety, data freshness, auth, and output semantics. The main gap is the unaddressed conflict between the stated npm/PyPI-only scope and the schema's cargo/go enum, plus the absence of explicit guidance for choosing between this and adjacent package security tools.

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?

Schema coverage is 100%, so the baseline is 3. However, the description states 'npm or PyPI package' and 'Uses PyPI JSON API and npm registry', while the schema's ecosystem enum explicitly includes cargo and go. This contradiction can mislead an agent into rejecting valid inputs. The description adds no beneficial parameter meaning beyond the schema and introduces an erroneous restriction.

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 states a specific verb ('Analyse ownership and release history'), identifies the resource ('npm or PyPI package'), and states the intended outcome ('detect supply-chain risk'). It clearly distinguishes this from sibling tools like security_fetch_package_vulnerabilities and security_fetch_package_risk_brief by focusing on maintainer and ownership history rather than vulnerabilities or general risk.

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?

It explicitly names the target audience ('security engineers auditing open-source dependencies before inclusion in production builds') and the intended use case. However, it does not mention when not to use this tool or explicitly contrast it with closely related siblings such as security_fetch_package_risk_brief or security_fetch_package_vulnerabilities.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.