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 agentmods add skills/0xranx/agentbrief/self-improvingnpx skills add 0xranx/agentbrief --skill self-improvinggit clone --depth 1 https://github.com/0xranx/agentbriefWrote 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/0xranx/agentbrief/self-improving)<a href="https://agentmods.dev/skills/0xranx/agentbrief/self-improving"><img src="https://agentmods.dev/badge/skills/0xranx/agentbrief/self-improving.svg" alt="Measured on agentmods" 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 | $0.00050 | $0.00561 |
| Opus 5 | $0.00025 | $0.00280 |
| Sonnet 5 | $0.00010 | $0.00112 |
| Haiku 4.5 | $0.00005 | $0.00056 |
Grade A, and why
self-improving 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 3d 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.
What it actually says
Self-Improving
You have a persistent learning system. Use it to get smarter over time.
When to Record a Learning
Record a learning when ANY of these happen:
- User corrects you — "no, use X instead of Y", "don't do that", "that's wrong"
- Something fails unexpectedly — a build error, test failure, or runtime crash reveals a project-specific gotcha
- You discover a non-obvious pattern — the codebase has a convention that isn't documented anywhere
- User expresses a preference — "I prefer X", "always do Y in this project", "never use Z"
Do NOT record:
- Generic programming knowledge (you already know this)
- Things already documented in CLAUDE.md or project docs
- Trivial one-time fixes
How to Record
Create a markdown file in .learnings/ at the project root:
# File naming: YYYY-MM-DD-short-description.md
.learnings/2026-03-20-use-pnpm-not-npm.md
Each learning file follows this format:
# Use pnpm, not npm
**Context**: Ran `npm install` and got lockfile conflicts.
**Correction**: This project uses pnpm exclusively. The `pnpm-lock.yaml` is the source of truth.
**Rule**: Always use `pnpm` for install, add, and run commands. Never use `npm` or `yarn`.
Keep it short — 3-5 lines. One learning per file.
How to Read Learnings
At the start of every conversation, check if .learnings/ exists. If it does, read all files in it before starting work. These are hard-won lessons from previous sessions — respect them.
.learnings/
├── 2026-03-18-api-auth-requires-bearer.md
├── 2026-03-19-tests-need-env-setup.md
└── 2026-03-20-use-pnpm-not-npm.md
Anti-patterns
- Don't create duplicate learnings — check existing files first
- Don't record learnings that contradict CLAUDE.md — CLAUDE.md wins
- Don't flood with trivial entries — quality over quantity
- Don't modify existing learnings unless the user explicitly corrects one
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.
- 3d ago First seen · 66 lines · 50 tokens per session scan A bca3b646d4a5
self-improving is a skill published in the GitHub repository 0xranx/agentbrief (45 stars, last pushed 5mo ago), licensed MIT. It adds 50 tokens to every session and 561 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
pptx
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ai-style
当任务是用中文撰写或改写面向读者的文案(产品发布稿、公众号文章、邮件、README 等), 或用户反馈文字「AI 味太重」「不像人写的」时,加载本 Skill。.
curly-quote-sft
Skill "curly-quote-sft" from bojieli/ai-agent-book, covering 中文技术文档符号与引用规范, 何时加载, 符号定义, 决策优先级 and 正反例约束.
triage
你是当前任务的分诊协调者。先识别用户的全部目标、顺序依赖和验收条件,再按 “事实检索 → 计算/执行 → 写作”顺序逐步请求切换到需要的专业能力。不要替专业 能力完成它的工作,也不要在信息缺失时臆造结果。.
writing
将共享历史中的已验证事实和计算结果整理成符合受众、格式与长度约束的成稿。.
research
用真实检索工具查找可追溯的事实、数据和来源。.