Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vladolaru/claude-code-plugins --skill prompt-engineergit clone --depth 1 https://github.com/vladolaru/claude-code-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vladolaru/claude-code-plugins/prompt-engineer)<a href="https://agentmods.dev/skills/vladolaru/claude-code-plugins/prompt-engineer"><img src="https://agentmods.dev/badge/skills/vladolaru/claude-code-plugins/prompt-engineer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vladolaru/claude-code-plugins/prompt-engineer"><img src="https://agentmods.dev/badge/skills/vladolaru/claude-code-plugins/prompt-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.04729 |
| Opus 5 | $0.00021 | $0.02364 |
| Sonnet 5 | $0.00008 | $0.00946 |
| Haiku 4.5 | $0.00004 | $0.00473 |
Grade A, and why
prompt-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 537 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Directory
Resolve SKILL_DIR to the absolute directory containing this SKILL.md, as
shown by the current host, before using any bundled path below.
Before a shell command uses $SKILL_DIR, assign it in that command or replace
it with the resolved path. It is not a host-exported environment variable.
Prompt Optimizer
Optimizes system prompts by applying research-backed prompt engineering patterns. This skill operates through human-in-the-loop phases: understand, plan, propose changes, receive approval, then integrate.
Purpose and Success Criteria
A well-optimized prompt achieves three things:
- Behavioral clarity: The agent knows exactly what to do in common cases and how to handle edge cases.
- Appropriate scope: Complex tasks get systematic decomposition; simple tasks don't trigger overthinking.
- Grounded changes: Every modification traces to a specific pattern with documented behavioral impact.
Optimization is complete when:
- Every change has explicit pattern attribution from the reference document
- No section contradicts another section
- The prompt matches its operating context (tool-use vs. conversational, token constraints, failure modes)
- Human has approved both section-level changes and full integration
When to Use This Skill
Use when the user provides a prompt and wants it improved, refined, or reviewed for best practices.
Do NOT use for:
- Writing prompts from scratch (different skill)
- Prompts that are already working well and user just wants validation (say so, don't force changes)
- Non-prompt content (documentation, code, etc.)
Required Resources
Before ANY analysis, read the appropriate pattern reference(s). Each reference contains a Technique Selection Guide table mapping domains, trigger conditions, stacking compatibility, conflicts, and expected effects.
Single-Turn Reference (Always Read)
$SKILL_DIR/references/prompt-engineering-single-turn.md
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 537 lines · 42 tokens per session scan A f0c4b275169e
prompt-engineer is a skill published in the GitHub repository vladolaru/claude-code-plugins (8 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 4,729 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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