Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add pitimon/8-habit-ai-dev/plugin install 8-habit-ai-devWrote 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/pitimon/8-habit-ai-dev/breakdown)<a href="https://agentmods.dev/skills/pitimon/8-habit-ai-dev/breakdown"><img src="https://agentmods.dev/badge/skills/pitimon/8-habit-ai-dev/breakdown.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 5.1 | $0.00045 | $0.02403 |
| Opus 5 | $0.00023 | $0.01202 |
| Sonnet 5 | $0.00009 | $0.00481 |
| Haiku 4.5 | $0.00005 | $0.00240 |
Grade A, and why
breakdown 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 6d 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Step 3: Plan (หั่นงานเป็นชิ้นเล็ก)
Habit: H3 — Put First Things First | Anti-pattern: One giant prompt that tries to do everything at once
Process
-
Read the requirements/design: Load PRD or design decisions from previous steps.
-
Decompose into atomic tasks (1 task = 1 focused unit of work):
## Task List 1. [ ] [Task name] — [1-sentence description] | Files: [list] | Depends on: [none or #N] 2. [ ] [Task name] — [1-sentence description] | Files: [list] | Depends on: [#1] ...For backlog-bound work, prefer vertical slices: each task should deliver a thin but complete path that can be verified or demonstrated on its own. Avoid horizontal layer tasks (
schema only,API only,UI only) unless that layer is independently useful and has its own acceptance criteria. A good issue describes end-to-end behavior, not a list of implementation layers. -
Prioritize by importance, not interest:
- Q1 (Urgent + Important): Blocking dependencies, security fixes
- Q2 (Important, Not Urgent): Core features, tests, docs
- Q3 (Urgent, Not Important): Nice-to-have polish
- Q4 (Neither): Skip entirely
-
Identify parallel work, delegation readiness, and classify orchestration: Tasks with no dependencies can run simultaneously. Also classify whether a task is ready for agent pickup or still needs human input.
Type When Isolation sequentialOutput of A feeds input of B Run after dependency completes parallel-safeTasks touch completely different files Same repo, concurrent execution parallel-worktreeTasks touch overlapping files or shared config Each agent gets isolated git worktree Produce an orchestration table for the task list:
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.
- 6d ago First seen · 161 lines · 45 tokens per session scan A 8c8b6c10c79f
breakdown is a skill published in the GitHub repository pitimon/8-habit-ai-dev (3 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 2,403 once invoked, about $0.0002 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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Situational awareness — where am I, what was I doing, what's next. Context recovery after compression, confusion, or mid-session reorientation.
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FastAPI best practices + Pydantic. Use when building or reviewing FastAPI APIs.