Content
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A strong, actionable body with executable code, a validated workflow, and well-structured one-level-deep references. The main weakness is conciseness: repeated inline URL citations and a partly redundant References section add tokens.
Suggestions
Cite each external URL once at first use and drop the repeated inline 'Per [github.com/...]' / '([arx.deidentifier.org/...])' restatements later in the body.
Trim the 'References' section to only links not already given inline, or convert the inline citations into the single References list to avoid stating each URL twice.
In the Overview, the academic citations ('Sweeney 2002, cited in NIST ...', 'Machanavajjhala et al. 2007') could be shortened to the NIST section pointer to save tokens without losing usefulness.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient and actionable, but the same pycanon/ARX URLs are repeated inline many times and the final 'References' section restates links and class names already cited above, adding tokens that could be tightened. | 2 / 3 |
Actionability | Provides fully executable pip install commands, a copy-paste pycanon Python snippet, a YAML policy example, and complete gate-script / ARX Java code in the referenced files, matching the score-3 'copy-paste ready' anchor. | 3 / 3 |
Workflow Clarity | The 7-step 'How to use' sequence has explicit validation (CI gate exits non-zero on breach) and a feedback loop (Step 6/7: fail -> re-mask with ARX -> re-verify), reinforced by the worked example and anti-patterns table. | 3 / 3 |
Progressive Disclosure | SKILL.md is a concise overview with well-signaled one-level-deep references to references/ci-gate.md and references/arx-api.md (both real files), plus a clear References section, matching the score-3 anchor. | 3 / 3 |
Total | 11 / 12 Passed |