Content
78%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.
A well-structured instruction-only skill: the 800-30 workflow is sequenced with concrete per-step outputs, a defined report schema, and a properly factored bundle (standards reference, worked template, scoring script) referenced one level deep. The main gaps are minor: no explicit script invocation or sample input in the body, a redundant Key Concepts table, and no validation loop between scoring and communicating results.
Suggestions
Show the actual process.py invocation from its docstring (e.g., `python scripts/process.py --input risks.json --output register.md --fail-on High`) and point to a minimal risk-input JSON example so the scoring step is copy-paste executable.
Trim or merge the 'Key Concepts' table into the workflow steps, where threat sources, events, vulnerabilities, and likelihood are already defined, to remove duplicated definitions.
Add an explicit validation checkpoint between Step 2 and Step 3 — e.g., re-check assessed likelihoods against incident history/threat intel and confirm every register entry has an owner before publishing the risk register.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is efficient — terse tables ('Threat source | The cause of a threat event: adversarial, accidental, structural, or environmental') and compact bullets dominate, but the 'Key Concepts' table re-explains terms already operationalized in the workflow steps (threat sources/events/vulnerabilities are defined in both Section 2a–2c and the table), and asides like '(Maturity tells you how mature your practices are; a risk assessment tells you what could hurt you and how badly)' pad slightly. This matches anchor 4 (efficient with minor over-explanation that could be trimmed), not 5 — a leaner version would cut the redundant definitions table. | 4 / 5 |
Actionability | Concrete guidance throughout: specific taxonomy steps ('Classify by type: Adversarial... Accidental... Structural... Environmental'), an explicit output table schema ('ID, threat event, asset, likelihood, impact, risk level, contributing vulnerabilities, recommended treatment, owner, residual risk'), and a named script ('Use `scripts/process.py` to score the register from a risk-input JSON... rank risks, and emit the register table'). It stops short of anchor 5 because the actual invocation command (`python process.py --input risks.json [--fail-on High]`) is never shown in the body, and no sample risk-input JSON appears in SKILL.md even though process.py requires one. | 4 / 5 |
Workflow Clarity | The five-step workflow is clearly sequenced (Prepare → Conduct 2a–2f → Communicate → Maintain → Treatment) with per-step outputs and an early checkpoint ('Lock these now' for the risk model/scales, 'Agreement on the risk model and scales before scoring'). This is anchor 4: clear sequence with most checkpoints present but minor validation gaps — there is no explicit review/validation loop after scoring (e.g., sanity-check likelihoods against incident data or re-validate register entries) before communicating results; not 3 because the sequence and checkpoints are far more complete than a bare step list. | 4 / 5 |
Progressive Disclosure | The body is a well-organized overview with three real, one-level-deep bundle files, each cited exactly where needed: '`references/standards.md`' (prerequisites, scales/matrix), '`assets/template.md`' (output format), and '`scripts/process.py`' (register scoring). Bulk detail (taxonomy tables, worked example, scoring engine) is appropriately split out rather than inlined, matching anchor 5 (clear overview with well-signaled one-level-deep references). | 5 / 5 |
Total | 17 / 20 Passed |