get_trust_signals

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

Beyond the annotations (read-only, idempotent, non-destructive), the description adds valuable behavioral context: it runs 4 backend endpoints in parallel and each returned field may be null if a backend call fails. This discloses performance characteristics and partial failure behavior, which is helpful for agents.

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 four sentences, each with a distinct purpose: scope, use cases, execution model, and return structure. There is no redundancy or filler, and the most important information is front-loaded.

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 composite read-only tool with no output schema, the description fully covers what it does, when to use it, how it executes (parallel), and what it returns (keys and null behavior). It provides enough context for an agent to select and invoke the tool correctly.

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 description coverage is 0%, so the description must compensate. It only indirectly references 'package' through 'deep-vetting a package' and does not explain the 'package' or 'ecosystem' parameters, their formats, or how they are used. The ecosystem enum is self-documenting, but package semantics are underspecified.

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 it aggregates all non-CVE supply-chain trust signals (maintainer trust, OpenSSF Scorecard, quality, provenance), using a specific verb ('aggregate') and resource. It distinguishes itself from sibling tools like get_vulnerabilities and get_health_score by focusing on non-CVE signals.

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 provides explicit USE WHEN guidance: deep-vetting a package beyond CVEs, hardened/regulated environments, SBOM/compliance, small-pkg ownership review, and choosing between healthy candidates. It implies exclusion of CVE-only use cases but does not explicitly name alternative tools or state when not to use it.

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