gavaza_assess

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

With no annotations, the description carries the full burden. It discloses that the tool writes a results JSON (via the `out` parameter) and that it reads an answers file, but it does not mention side effects, prerequisites, error behavior, or file-modification possibilities. It also doesn't clarify whether it mutates the input file. This partial disclosure earns a 3.

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 compact and efficiently structured. It leads with the core purpose, then explains each parameter in separate backtick-delimited sections. Every sentence carries necessary information, with no fluff or repetition.

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 the tool's low complexity (two flat parameters, no nested objects) and the presence of an output schema, the description covers the essentials: what it does, the input format, and the output location. It omits contextual links to other tools (e.g., whether the questionnaire must be generated first), but this is not critical for this tool's operation.

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 fully. It defines `answers` as a path to a JSON file mapping item ids to 'yes'|'no'|'partial' and explains that `out` overrides the output location. This adds substantial semantic meaning beyond the bare schema types, making both parameters understandable.

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 opens with a clear, specific verb-resource pairing: 'Run the POPIA compliance questionnaire'. It clearly states the tool takes a JSON answers file, which distinguishes it from sibling tools like gavaza_generate (which likely generates the questionnaire) and gavaza_report (which reports on it).

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 the use case: when you have a JSON answers file and want to execute the assessment. It does not explicitly name alternatives or exclusions, but the input format and purpose are clear enough that an agent can infer when to use it. A explicit comparison to gavaza_generate or gavaza_report would have warranted a 5.

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