prompt-engineering
Verdict safe, but 1 finding (1 info), mainly policy violation. Most recent scan 2026-10-22.
This is a byte-identical copy of prompt-engineering from 101-skills, which is the primary page for this skill. Same SKILL.md, same files; each copy is scanned separately so divergence shows up here.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Master prompt engineering for AI models: LLMs, image generators, video models. Techniques: chain-of-thought, few-shot, system prompts, negative prompts. Models: Claude, GPT-4, Gemini, FLUX, Veo, Stable Diffusion prompting. Use for: better AI outputs, consistent results, complex tasks, optimization. Triggers: prompt engineering, how to prompt, better prompts, prompt tips, prompting guide, llm prompting, image prompt, ai prompting, prompt optimization, prompt template, prompt structure, effective prompts, prompt techniques
- Package
- 1 file, 9.5 KB
- SKILL.md
- 1284 words, 12+ sections
- Code
- None. Instructions only.
- Allowed tools
Bash(belt*)
SKILL.md covers: Prompt Engineering Guide · Quick Start · Well-structured LLM prompt · LLM Prompting · Basic Structure · Role Prompting · Task Clarity · Bad: vague · Good: specific · Chain-of-Thought · Few-Shot Examples · Output Format Specification
Findings
INFO Skill does not specify a license Policy Violationstatic
Skill manifest does not include a 'license' field. Specifying a license helps users understand usage terms.
SKILL.md
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 9.5 KB |
External hosts referenced
cloud.inference.sh inference.sh raw.githubusercontent.com
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22 at commit becc25649700. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/magentosh/superpowers
- Raw scan result: magentosh-superpowers-guides-prompting-prompt-engineering-scan.json
- Badge for your README:
- Request a re-scan