patch_compliance

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

With no annotations, the description fully discloses behavioral traits: read-only operation, exact string match for compliance (not version semantics), injected-only data, return fields, and defaults. No side effects or hidden behaviors are omitted.

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 well-structured with summary, details, parameter docs, return dict, and example. It is slightly verbose but each sentence adds value. Could be slightly more concise, but overall efficient.

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?

Given no output schema and only 3 parameters, the description adequately covers input, algorithm, output fields, and an example. It lacks error handling or edge cases, but for a compliance tool it is sufficiently complete.

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 0%, but the description provides detailed parameter explanations: endpoints as injected inventory, target_patch with fleet-majority default, and sla_pct with 95.0 default. An example further clarifies usage, adding significant value beyond the bare schema.

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 tool's purpose: computing patch-compliance SLA as a percentage of the fleet on target patch level, with a verdict and non-compliant list. It distinguishes from patch_status by reframing it as a compliance metric, and specifies it is injected-only and not a live collection.

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 usage for SLA compliance analysis but does not explicitly contrast with sibling tools like drift_report or patch_status. It notes injected endpoints are required, but does not provide explicit when-to-use or when-not-to-use guidance.

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