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 unrealandychan/clean-code-skill --skill growth-loggit clone --depth 1 https://github.com/unrealandychan/clean-code-skillWrote 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/unrealandychan/clean-code-skill/growth-log)<a href="https://agentmods.dev/skills/unrealandychan/clean-code-skill/growth-log"><img src="https://agentmods.dev/badge/skills/unrealandychan/clean-code-skill/growth-log/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/unrealandychan/clean-code-skill/growth-log"><img src="https://agentmods.dev/badge/skills/unrealandychan/clean-code-skill/growth-log.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 | $0.00034 | $0.01517 |
| Opus 5.5 | $0.00014 | $0.00607 |
| Sonnet 5.5 | $0.00007 | $0.00303 |
| Haiku 4.5 | $0.00003 | $0.00152 |
Grade A, and why
growth-log 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 1mo 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.
This is a copy
94% identical to growth-log — 26 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Growth Log Skill
The problem: Most people write "fixed a bug in X" as a learning log. That's a diary entry, not a learning artifact. A real growth log extracts the pattern so you recognize it next time.
This skill teaches: How to write learning entries that compound across sessions. Works with any note-taking system — Markdown files, Notion, Obsidian, plain text. Templates are generic; adapt to your setup.
When to Activate
- After completing a complex task (multi-file, new feature, architecture change)
- After a failure, mistake, or "that was harder than expected" moment
- When you want to review what you've learned over a period
When NOT to activate: Trivial changes (typo fixes, single-line tweaks, config value changes with no debugging). The threshold: did this task involve debugging, redoing, rollback, or a non-obvious decision? If yes → write an entry. If no → skip.
The Three Rules
Rule 1: Failures > Achievements
A failure is nutritionally denser than a success. One bug that took 2 hours to find teaches more than 3 features that worked first try.
Bad: "Successfully implemented the login flow."
Good (web dev): "Login flow: session token wasn't persisting because the cookie SameSite defaulted to Lax in Chrome 128+. Pattern: always explicitly set SameSite=None; Secure when cross-origin. Signal to recognize: auth breaks after browser upgrade or when crossing origin boundaries."
Good (data pipeline): "CSV import failed silently on empty rows because pandas.read_csv(dropna=False) keeps zero-width rows that len() counts as valid. Pattern: always df.dropna(how='all', inplace=True) before row-count validation."
Rule 2: The Bole Principle (伯乐原则)
Before writing a new entry, ask: "Is this fundamentally the same as something I already recorded?"
Same root cause, different symptom → merge, don't duplicate. New root cause → new entry.
How to check: Search existing entries for keywords from your root cause before writing. If you find a match, add your new symptom as an additional example under the existing entry rather than creating a duplicate.
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.
- 1mo ago First seen · 129 lines · 34 tokens per session scan A 8f90db7c9e84
growth-log is a skill published in the GitHub repository unrealandychan/clean-code-skill (12 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 1,517 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to growth-log, differing in 26 lines, and is treated as a copy.
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