Content
86%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is a model of token efficiency: deterministic rules, a defined output format, and a hard blocking rule, organized into clean sections. The only gaps are a missing worked example and implicit edge-case handling for how risk modifiers combine.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Every line instructs ('Read-only or local = low.', '+1 level for write access.', 'OVERRIDE NOT ALLOWED.') with zero padding and no explanation of concepts Claude already knows — lean and efficient throughout. | 5 / 5 |
Actionability | Concrete, executable decision rules ('Assign risk level: low, medium, high, critical', 'Output `AI Risk Assessment: {LEVEL}`', 'CRITICAL: block execution') with per-level escalation actions. Not a 5 because no worked example is given (e.g. prod DB with write access = critical) and edge rules are implicit — how the +1 modifiers stack or cap, and what a read-only production environment scores. | 4 / 5 |
Workflow Clarity | A clear numbered sequence (steps 1–10) with an explicit escalation ladder serving as checkpoints ('MEDIUM: warn user...', 'CRITICAL: block execution, require external risk reduction'). Not a 5 because re-validation on state change appears only as a pitfall ('Not re-assessing when new environments join mid-session') rather than as a process step with a feedback loop. | 4 / 5 |
Progressive Disclosure | The body is under 30 lines, self-contained, and organized into well-labeled sections (`process`, `pitfalls`); no external references are needed, so the simple-skill guideline applies. | 5 / 5 |
Total | 18 / 20 Passed |