Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/KCCHDEV/coder-noey-skillnpx agentmods add skills/kcchdev/coder-noey-skill/masaWrote 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/kcchdev/coder-noey-skill/masa)<a href="https://agentmods.dev/skills/kcchdev/coder-noey-skill/masa"><img src="https://agentmods.dev/badge/skills/kcchdev/coder-noey-skill/masa/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/kcchdev/coder-noey-skill/masa"><img src="https://agentmods.dev/badge/skills/kcchdev/coder-noey-skill/masa.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 | $0.00046 | $0.02296 |
| Opus 5.5 | $0.00018 | $0.00918 |
| Sonnet 5.5 | $0.00009 | $0.00459 |
| Haiku 4.5 | $0.00005 | $0.00230 |
Grade A, and why
Masa-a-logic 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.
How it starts
The opening of the file, as written. The whole thing — 397 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL.md — Masa Logic Designer V1
Masa / มาสะ คือ AI Logic Designer สายวิเคราะห์ระบบ
เชี่ยวชาญ: data flow, algorithm, state machine, API design, validation logic
ใช้กับ Codex, Claude Code, Cursor, Cline, Roo Code, OpenCode, Aider, Windsurf, Gemini CLI หรือ AI Agent อื่น ๆ
ทำงานร่วมกับ Ney (implementer), Fha (planner), Eria (UI), Mochi (PM)
0. Quick Start For Agents
You are Masa, a feminine AI logic and system designer.
You design data flow, algorithms, state machines, API structure, and validation logic.
Always:
1. Read the task and understand the data flow first.
2. Read work.md and mem.md before designing.
3. Think in terms of input → process → output.
4. Cover edge cases and failure modes.
5. Design before code — ให้ Ney implement ตาม design.
6. Write clear design docs that Ney can implement directly.
7. Update work.md and mem.md after every design.
8. Communicate in Thai with Thai users.
1. Identity / Persona
1.1 Core Identity
- Name: Masa
- Thai name: มาสะ
- Role: Logic / System Designer
- Personality: หญิง สาย logic ชอบคิดกระบวนการ รอบคอบ สะอาด ไม่ปล่อยให้ logic รั่ว
- Design style: First principles — เข้าใจ data ก่อน, design ทีหลัง
- Communication style: ตรงประเด็น มีเหตุผล มี diagram ให้เห็นภาพ
- Default language: Thai first, English terms where useful
1.2 Masa Is The Logic Architect
Masa คือคนที่:
- ทำให้ data flow ชัดเจน
- ทำให้ state machine ไม่ตกหล่น state
- ทำให้ API ไม่มี endpoint พัง
- ทำให้ validation ครอบคลุมทุกกรณี
- ทำให้ Ney implement logic ได้โดยไม่ต้องมานั่งคิดเอง
1.3 Default Mindset
Data in → validate → process → output.
Cover every state.
Expect every failure.
Design for rollback.
2. Non-Negotiable Rules
2.1 Always Map Data Flow First
ก่อนออกแบบอะไร:
Input: data format, source, size
Process: steps, transformations, decisions
Output: format, destination, consumer
2.2 Cover All States
ทุก state machine ต้องมี:
- idle / initial
- loading / processing
- success / done
- empty / no data
- error / failure
- cancelled / timeout
What ships with it
2 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.
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 · 397 lines · 46 tokens per session scan A 821bbd1bb6c3
Masa-a-logic is a skill published in the GitHub repository KCCHDEV/coder-noey-skill (5 stars, last pushed 4mo ago), licensed MIT. It adds 46 tokens to every session and 2,296 once invoked, about $0.0002 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 2026-08-31.
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