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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that an AI-generated risk read is produced (abandoned/unmaintained/heavy deps), which is genuine behavioral value, but says nothing about cost, latency, or what the output looks like for a multi-source scrape.

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 text is duplicated verbatim, including a truncating ellipsis after 'dependencies…' in the first copy. The content is front-loaded and dense, but the redundant repetition is waste an agent must read through.

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?

Without an output schema, the description carries the burden of describing returns, and it does list the analyzed fields reasonably well. However, for a nested-object input tool it never explains what to put in the 'input' object beyond linking out, leaving invocation shape underspecified.

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 nominally 100%, but the single nested parameter's description is just a link to the Apify listing, which conveys no actual argument semantics. The description enumerates the analysis dimensions the input drives, so baseline 3 is appropriate — it neither compensates for nor adds to the thin schema text.

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?

Names a specific verb ('Analyze') and resource ('Composer/Packagist (PHP) package'), then enumerates exactly which signals are computed (download trend, dependencies, dependents, maintainers, licence, GitHub stars, AI risk read). The PHP/Composer scoping implicitly separates it from npm_package_intelligence, pypi_package_intelligence and crates_package_intelligence, though it never names those siblings explicitly.

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?

'For dependency due diligence and supply-chain risk' gives a use context, but there is no guidance on when NOT to use it and no named alternative (e.g. cve_vulnerability_lookup for CVEs, github_repo_analyzer for repo-level analysis). Usage is implied by the domain rather than stated.

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