wong

wong is a skill for Claude Code, Codex from ShockRock2004/kamar-taj. It costs 144 tokens per session (4,918 once invoked), scanned A, original, MIT.

A daily learning guide that turns an AI coding agent's work across sessions and repositories into one dated Markdown file and a phone-readable PDF.

In plain words
What is it for?
Use it to study what was built, why decisions were made, and how to recreate the work, with the PDF uploaded to Google Drive.
Why use it?
It makes the day's work understandable and reusable instead of leaving only a short change log.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions subagents.

Good fit Use it to study what was built, why decisions were made, and how to recreate the work, with the PDF uploaded to Google Drive.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/shockrock2004/kamar-taj/wong
Install

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.

Any agent
npx skills add ShockRock2004/kamar-taj --skill wong
Clone the repo
git clone --depth 1 https://github.com/ShockRock2004/kamar-taj

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for wong

README.md
[![agentmods](https://agentmods.dev/badge/skills/shockrock2004/kamar-taj/wong/github.svg)](https://agentmods.dev/skills/shockrock2004/kamar-taj/wong)
Your own site
<a href="https://agentmods.dev/skills/shockrock2004/kamar-taj/wong"><img src="https://agentmods.dev/badge/skills/shockrock2004/kamar-taj/wong/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.

agentmods 80×15 button for wong

Your own site · 80×15
<a href="https://agentmods.dev/skills/shockrock2004/kamar-taj/wong"><img src="https://agentmods.dev/badge/skills/shockrock2004/kamar-taj/wong.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 144 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,918 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00144 $0.04918
Opus 5 $0.00072 $0.02459
Sonnet 5 $0.00029 $0.00984
Haiku 4.5 $0.00014 $0.00492

Measured 10d ago against content hash dae4b89fb2c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

wong 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 10d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (collect_day.py, render_pdf.sh, upload_to_drive.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

wong/SKILL.md · 367 lines

How it starts

The opening of the file, as written. The whole thing — 367 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Wong — end-of-day learning guidebook (formerly daily-log)

Turn a full day of Claude Code work (across every session and repo) into a single dated markdown file written as a teaching guide, so the user can genuinely learn the work: re-implement the code by hand, understand why each decision was made, and be able to explain how it works because they actually understand it.

The output is NOT a changelog. It is a beginner's textbook — written so simply and conversationally that someone with no software background could read it top to bottom and understand both what was done and why. Every technical term is defined in plain language the first time it appears; code stays technical but is wrapped in plain-English explanation. Depth and the "why" matter more than completeness of trivia. See the full Writing style — REQUIRED rules in step 4.

Step 0. Read the effort level from the command

The user may pass an effort level as the first argument: light, medium, or heavy. If none is given, default to heavy. (They may also pass a date; a YYYY-MM-DD token is the date, a light/medium/heavy token is the effort. Either order, both optional. e.g. /wong medium, /wong light 2026-06-25.)

Effort controls token usage — it scales BOTH the digest size (via --effort on the collector) AND how much you do while writing:

  • light — cheapest. Document only the top 2–3 pieces of work. Do not run git show/extra file reads; rely on the digest + commit messages, and include at most one short code snippet total. Keep each section brief. Still produce the Git skills section, Slack summary, PDF, and upload.
  • medium — balanced. Document the top ~5 pieces. Pull real code (git show) for only the 2–3 most important ones. Moderate depth.
  • heavy (default) — the full treatment described below: every distinct piece of work, pull real code for each, full depth.

Carry the chosen level through all steps.

Steps

1. Collect the day's raw material

Run the collector with the chosen effort (it reads every session transcript from disk, so it captures all concurrent/closed sessions, not just this one):

Read the full file on GitHub · 367 lines

Files

What ships with it

3 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.

Changes

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.

  1. 10d ago First seen · 367 lines · 144 tokens per session scan A dae4b89fb2c1

Subscribe to this mod's changes

wong is a skill published in the GitHub repository ShockRock2004/kamar-taj (4 stars, last pushed 1mo ago), licensed MIT. It adds 144 tokens to every session and 4,918 once invoked, about $0.0007 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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