Content
85%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 highly actionable, well-sequenced exploitation reference with strong feedback loops and copy-paste payloads, weakened only by its monolithic single-file structure that inlines content which could be progressively disclosed into per-engine reference files.
Suggestions
Split the per-engine deep-dives (Django context-processor map, blind/oracle sections) into one-level-deep reference files under references/ and link to them from a concise overview in SKILL.md.
Tighten the Django section's prose (e.g. the 'Critical: ... will NOT work' list) into a compact table to recover token budget.
Add a short 'Prerequisites / scope' note stating this targets authorized CTF/pentest contexts so the workflow's intent is explicit.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly lean, executable content that assumes Claude's competence (no generic 'what is a template engine' padding); a few prose-heavy stretches, notably the Django section, could be trimmed without losing actionability. | 4 / 5 |
Actionability | Fully copy-paste-ready curl commands per engine, a runnable python3 subclass-enumeration snippet, and concrete payloads covering the common cases, with necessary placeholders (<TARGET>, <INDEX>) clearly marked. | 5 / 5 |
Workflow Clarity | Clear detect→fingerprint→exploit sequencing per engine with explicit validation checkpoints and feedback loops: calibration steps, '3-strike pivot' rules, and decision flows for blind/oracle variants. | 5 / 5 |
Progressive Disclosure | No bundle files exist and the skill is a single ~308-line document; section headers give reasonable navigation, but engine-specific deep-dives (e.g. the large Django block) are inlined rather than split into one-level-deep reference files. | 3 / 5 |
Total | 17 / 20 Passed |