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 autohandai/community-skills --skill agentic-development-principlesgit clone --depth 1 https://github.com/autohandai/community-skillsWrote 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/autohandai/community-skills/agentic-development-principles)<a href="https://agentmods.dev/skills/autohandai/community-skills/agentic-development-principles"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/agentic-development-principles/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/autohandai/community-skills/agentic-development-principles"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/agentic-development-principles.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 | $0.00044 | $0.02165 |
| Opus 5.5 | $0.00018 | $0.00866 |
| Sonnet 5.5 | $0.00009 | $0.00433 |
| Haiku 4.5 | $0.00004 | $0.00216 |
Grade A, and why
agentic-development-principles 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 — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic development principles (Agentic Development Principles)
"AI is the copilot; you are the pilot" AI agents amplify the developer's thinking and take over repetitive work, but final decision-making authority and responsibility always remain with the developer.
When to use this skill
- When starting a collaboration session with an AI agent
- When deciding an approach before starting a complex task
- When establishing a context management strategy
- When reviewing workflows to improve productivity
- When onboarding teammates on how to collaborate with AI
- When applying baseline principles while adopting a new AI tool
Principle 1: Divide and conquer (Divide and Conquer)
Core concept
AI performs much better with small, clear instructions than with large, ambiguous tasks.
How to apply
| Wrong example | Right example |
|---|---|
| "Build me a login page" | 1. "Create the login form UI component" |
| 2. "Implement the login API endpoint" | |
| 3. "Wire up the authentication logic" | |
| 4. "Write test code" | |
| "Optimize the app" | 1. "Analyze performance bottlenecks" |
| 2. "Optimize database queries" | |
| 3. "Reduce frontend bundle size" |
Practical pattern: staged implementation
Step 1: Design and validate the model/schema
Step 2: Implement core logic (minimum viable functionality)
Step 3: Connect APIs/interfaces
Step 4: Write and run tests
Step 5: Integrate and refactor
Validation points
- Can each step be validated independently?
- If it fails, can you fix only that step?
- Is the scope clear enough for the AI to understand?
Principle 2: Context is like milk (Context is like Milk)
Core concept
Context (the AI's working memory) should always be kept fresh and compact.
- Old and irrelevant information reduces AI performance
- Context drift: mixing multiple topics can reduce performance by up to 39% (research)
Context management strategies
Strategy 1: Single-purpose conversation
Session 1: Work on the authentication system
Session 2: Work on UI components
Session 3: Write test code
Session 4: DevOps/deployment work
- Do not mix multiple topics in a single conversation
- Start a new session for a new topic
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 · 300 lines · 44 tokens per session scan A 9a37ec0b21e4
agentic-development-principles is a skill published in the GitHub repository autohandai/community-skills (11 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 44 tokens to every session and 2,165 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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