AI Agent Skills is a curated library and package manager for installing, organizing, and creating skills for compatible AI coding agents. It is for developers who want to manage reusable agent instructions through a command-line or terminal interface. The catalogue skills and agents are examples of the kind of add-ons it helps manage.
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 MoizIbnYousaf/Ai-Agent-Skills --skill best-practicesgit clone --depth 1 https://github.com/MoizIbnYousaf/Ai-Agent-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/moizibnyousaf/ai-agent-skills/best-practices)<a href="https://agentmods.dev/skills/moizibnyousaf/ai-agent-skills/best-practices"><img src="https://agentmods.dev/badge/skills/moizibnyousaf/ai-agent-skills/best-practices/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/moizibnyousaf/ai-agent-skills/best-practices"><img src="https://agentmods.dev/badge/skills/moizibnyousaf/ai-agent-skills/best-practices.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 104 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 424 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00035 | $0.04006 |
| Opus 5 | $0.00017 | $0.02003 |
| Sonnet 5 | $0.00007 | $0.00801 |
| Haiku 4.5 | $0.00003 | $0.00401 |
Grade A, and why
best-practices 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 11d 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 — 502 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Best Practices — Prompt Transformer
Transform prompts by adding what Claude needs to succeed.
Start Here
Based on user's request:
User provides a prompt to transform: → Ask using AskUserQuestion:
- Question: "How should I improve this prompt?"
- Header: "Mode"
- Options:
- Transform directly — "I'll apply best practices and output an improved version"
- Build context first — "I'll gather codebase context and intent analysis first"
User asks to learn/understand: → Show the 5 Transformation Principles section
User asks for examples: → Link to references/before-after-examples.md
User asks to evaluate a prompt: → Use the Success Criteria eval rubric at the end of this document
If "Transform directly"
Apply the 5 principles below and output the improved prompt immediately.
If "Build context first"
Launch 3 parallel agents to gather context:
Run these agents IN PARALLEL using the Task tool:
- Task task-intent-analyzer("[user's prompt]")
- Task best-practices-referencer("[user's prompt]")
- Task codebase-context-builder("[user's prompt]")
What Each Agent Returns
| Agent | Mission | Returns |
|---|---|---|
| task-intent-analyzer | Understand what user is trying to do | Task type, gaps, edge cases, transformation guidance |
| best-practices-referencer | Find relevant patterns from references/ | Matching examples, anti-patterns to avoid, transformation rules |
| codebase-context-builder | Explore THIS codebase | Specific file paths, similar implementations, conventions |
After Agents Return
- Synthesize findings — Combine intent + best practices + codebase context
- Apply matching patterns — Use examples from best-practices-referencer as templates
- Ground in codebase — Add specific file paths from codebase-context-builder
- Transform the prompt — Apply the 5 principles with all gathered context
- Output — Show improved prompt with before/after comparison
What ships with it
8 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.
- agents/best-practices-referencer.md 9.2 KB
- agents/codebase-context-builder.md 10 KB
- agents/task-intent-analyzer.md 9.6 KB
- references/anti-patterns.md 13 KB
- references/before-after-examples.md 27 KB
- references/best-practices-guide.md 32 KB
- references/common-workflows.md 14 KB
- references/prompt-patterns.md 11 KB
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.
- 11d ago First seen · 502 lines · 35 tokens per session scan A 4fd62ab3cccc
best-practices is a skill published in the GitHub repository MoizIbnYousaf/Ai-Agent-Skills (1,134 stars, last pushed 24d ago), licensed MIT. It adds 35 tokens to every session and 4,006 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 2026-08-30.
Other skills, from other repositories
v4-best-practices
Use when working with deepseek-v4-pro or deepseek-v4-flash in thinking mode on multi-step or plan-driven tasks. Provides rules to prevent stale references, unverified plan assumptions, and vague plan output.
firebase-ai
Use when setting up firebaseai, generating text/chat with Gemini, streaming AI output, building multimodal prompts, or handling AI errors.
sqlite-vec-skilld
ALWAYS use when writing code importing "sqlite-vec". Consult for debugging, best practices, or modifying sqlite-vec, sqlite vec.
nativeprompt
A prompt editor that adapts a user's request to the rules of a selected coding model, such as Claude Code, Codex, Gemini CLI, or GPT-5.
refine
Transform a brief or prompt into a structured, production-ready prompt via prompt-optimizer. File or text mode.
coding-agents-prompt-authoring
To author, adapt, review, and validate prompts (skills, agents, workflows, rules, etc.) with brief, contracts, and a validation pack.