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 Ckokoski/AuthorAgent --skill self-improvegit clone --depth 1 https://github.com/Ckokoski/AuthorAgentWrote 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/ckokoski/authoragent/self-improve)<a href="https://agentmods.dev/skills/ckokoski/authoragent/self-improve"><img src="https://agentmods.dev/badge/skills/ckokoski/authoragent/self-improve/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/ckokoski/authoragent/self-improve"><img src="https://agentmods.dev/badge/skills/ckokoski/authoragent/self-improve.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 | $0.00026 | $0.01658 |
| Opus 5.5 | $0.00010 | $0.00663 |
| Sonnet 5.5 | $0.00005 | $0.00332 |
| Haiku 4.5 | $0.00003 | $0.00166 |
Grade A, and why
self-improve 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 2mo 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 — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Improvement Loop — Core Skill
AuthorAgent gets better every time it works. This skill creates a persistent learning loop where the agent tracks what works, what fails, and what the user prefers — then applies those lessons to future tasks.
How It Works
The Loop
┌─────────────────────────────┐
│ │
│ 1. DO THE WORK │
│ (goal step, writing, │
│ research, etc.) │
│ │
└──────────┬──────────────────┘
│
▼
┌─────────────────────────────┐
│ │
│ 2. OBSERVE RESULT │
│ Did the user accept it? │
│ Did they revise it? │
│ Did it trigger an error? │
│ How long did it take? │
│ │
└──────────┬──────────────────┘
│
▼
┌─────────────────────────────┐
│ │
│ 3. EXTRACT LESSON │
│ What specifically │
│ went right or wrong? │
│ What pattern emerges? │
│ │
└──────────┬──────────────────┘
│
▼
┌─────────────────────────────┐
│ │
│ 4. STORE LESSON │
│ Write to learning log │
│ (workspace/memory/ │
│ improvement-log.jsonl) │
│ │
└──────────┬──────────────────┘
│
▼
┌─────────────────────────────┐
│ │
│ 5. APPLY LESSONS │
│ Before each new task, │
│ check the log for │
│ relevant lessons and │
│ adjust behavior │
│ │
└──────────┬──────────────────┘
│
└──────── back to step 1
What Gets Tracked
Every lesson entry in improvement-log.jsonl contains:
{
"id": "lesson-042",
"timestamp": "2026-02-24T14:30:00Z",
"category": "writing",
"trigger": "user_revision",
"context": "Chapter 3 of thriller project",
"observation": "User rewrote all dialogue tags from creative tags to simple said/asked",
"lesson": "This user strongly prefers invisible dialogue tags (said/asked). Do not use creative tags like 'exclaimed', 'muttered', 'hissed' unless the user specifically asks.",
"confidence": 0.9,
"applied_count": 0,
"source": "user_feedback"
}
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.
- 2mo ago First seen · 218 lines · 26 tokens per session scan A 0666910a6239
self-improve is a skill published in the GitHub repository Ckokoski/AuthorAgent (124 stars, last pushed 4mo ago), licensed MIT. It adds 26 tokens to every session and 1,658 once invoked, about $0.0001 per session on Opus 5.5. 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.
self-improve compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| self-improveCkokoski/AuthorAgent | Skill | 124 | 4mo ago | MIT | A | 26 | Claude Code, Codex |
| awesome-chatgpttaishi-i/awesome-ChatGPT-repositories | Skill | 3.4k | yesterday | CC0-1.0 | A | 79 | Claude Code |
| awesome-chatgpt-searchtaishi-i/awesome-ChatGPT-repositories | Skill | 3.4k | yesterday | CC0-1.0 | B | 63 | Claude Code, Codex |
| api-to-examplesurfmind-space/awesome-surfmind | Skill | 8 | 7d ago | MIT | A | 75 | Claude Code, Codex |
| code-translatorsurfmind-space/awesome-surfmind | Skill | 8 | 7d ago | MIT | A | 65 | Claude Code, Codex |
| dev-toolkitRbBtSn0w/awesome-copilot-mcp | Skill | 4 | today | MIT | A | 17 | Claude Code, Codex |
| deal-checkersurfmind-space/awesome-surfmind | Skill | 8 | 7d ago | MIT | A | 77 | Claude Code, Codex |