Borrowing it
Nothing to install: this file belongs to pskoett/measuring-ai-proficiency. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/pskoett/measuring-ai-proficiency/main/.claude/skills/simplify-and-harden/SKILL.mdgit clone --depth 1 https://github.com/pskoett/measuring-ai-proficiencyWrote 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/pskoett/measuring-ai-proficiency/simplify-and-harden)<a href="https://agentmods.dev/skills/pskoett/measuring-ai-proficiency/simplify-and-harden"><img src="https://agentmods.dev/badge/skills/pskoett/measuring-ai-proficiency/simplify-and-harden/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/pskoett/measuring-ai-proficiency/simplify-and-harden"><img src="https://agentmods.dev/badge/skills/pskoett/measuring-ai-proficiency/simplify-and-harden.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00071 | $0.05488 |
| Opus 5 | $0.00036 | $0.02744 |
| Sonnet 5 | $0.00014 | $0.01098 |
| Haiku 4.5 | $0.00007 | $0.00549 |
Grade A, and why
simplify-and-harden 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 11d 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 — 520 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Skill: Simplify & Harden
Install
npx skills add pskoett/pskoett-ai-skills/skills/simplify-and-harden
For CI-only execution, use:
npx skills add pskoett/pskoett-ai-skills/skills/simplify-and-harden-ci
Metadata
| Field | Value |
|---|---|
| Skill ID | simplify-and-harden |
| Version | 0.1.0 |
| Trigger | Post-completion hook |
| Author | Peter Skøtt Pedersen |
| Category | Code Quality / Security |
| Priority | Recommended |
Rationale and Philosophy
When a coding agent completes a task, it holds peak contextual understanding of the problem, the solution, and the tradeoffs it made along the way. This context degrades immediately -- the next task wipes the slate. Simplify & Harden exploits that peak context window to perform two focused review passes before the agent moves on.
Most agents solve the ticket and stop. This skill turns "done" into "done well."
The operating philosophy is a deliberate "fresh eyes" self-review before moving on: carefully re-read all newly written code and all existing code modified in the task, and look hard for obvious bugs, errors, confusing logic, brittle assumptions, naming issues, and missed hardening opportunities. The goal is not to expand scope or rewrite the solution -- it is to use peak context to perform a disciplined first review pass while the agent still remembers the intent behind every change.
Best Use with Independent Review
This skill is a post-completion self-pass and does not replace an independent review pass.
Recommended flow:
- Implement the task.
- Run Simplify & Harden to clean, harden, and document non-obvious decisions.
- Run an independent review pass for severity-ordered findings.
- Merge only after both passes are addressed.
If the two disagree, treat the independent review findings as the external gate and either fix or explicitly waive findings.
What ships with it
1 file 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.
- 11d ago First seen · 520 lines · 71 tokens per session scan A 714e8514921a
simplify-and-harden is a skill published in the GitHub repository pskoett/measuring-ai-proficiency (11 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 5,488 once invoked, about $0.0004 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 2026-08-31.
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