using-agent-skills
Lets your agent discover and use the right skill for the job. It's useful at the start of each conversation to ensure efficiency.
What it does
This 'skill' helps the AI choose the right tool for the job. It organizes various 'skills' (tools) by software development task type, so the AI can find and use the most suitable one.
When to use it
- ✓When you want the AI to help write code.
- ✓When you need the AI to review existing code.
- ✓When you want the AI to help plan a software project.
Example of what to ask your AI
“I need help writing code for a website. Which skill should I use?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The AI analyzes your task and compares it with the different 'skills' available. Each 'skill' is like a specialized toolbox for a phase of development, such as writing code, testing, or fixing errors.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill using-agent-skillsOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/using-agent-skills/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Bundled upstream support
Supporting files are included at skill-relative paths. See UPSTREAM-NOTICE.md for their pinned sources, licenses, hashes, and import changes.
Using Agent Skills
Overview
Agent Skills is a collection of engineering workflow skills organized by development phase. Each skill encodes a specific process that senior engineers follow. This meta-skill helps you discover and apply the right skill for your current task.
Skill Discovery
When a task arrives, identify the development phase and apply the corresponding skill:
Task arrives
│
├── Don't know what you want yet? ──────→ interview-me
├── Have a rough concept, need variants? → idea-refine
├── New project/feature/change? ──→ spec-driven-development
├── No quality bar written down? ──→ constraint-driven-development
├── Have a spec, need tasks? ──────→ planning-and-task-breakdown
├── Implementing code? ────────────→ incremental-implementation
│ ├── UI work? ─────────────────→ frontend-ui-engineering
│ ├── API work? ────────────────→ api-and-interface-design
│ ├── Need better context? ─────→ context-engineering
│ ├── Need doc-verified code? ───→ source-driven-development
│ └── Stakes high / unfamiliar code? ──→ doubt-driven-development
├── Writing/running tests? ────────→ test-driven-development
│ └── Browser-based? ───────────→ browser-testing-with-devtools
├── Something broke? ──────────────→ debugging-and-error-recovery
├── Reviewing code? ───────────────→ code-review-and-quality
│ ├── Too complex? ─────────────→ code-simplification
│ ├── Security concerns? ───────→ security-and-hardening
│ └── Performance concerns? ────→ performance-optimization
├── Committing/branching? ─────────→ git-workflow-and-versioning
├── CI/CD pipeline work? ──────────→ ci-cd-and-automation
├── Deprecating/migrating? ────────→ deprecation-and-migration
├── Writing docs/ADRs? ───────────→ documentation-and-adrs
├── Adding logs/metrics/alerts? ───→ observability-and-instrumentation
└── Deploying/launching? ─────────→ shipping-and-launch
Core Operating Behaviors
These behaviors apply at all times, across all skills. They are non-negotiable.
1. Surface Assumptions
Before implementing anything non-trivial, explicitly state your assumptions:
ASSUMPTIONS I'M MAKING:
1. [assumption about requirements]
2. [assumption about architecture]
3. [assumption about scope]
→ Correct me now or I'll proceed with these.
Don't silently fill in ambiguous requirements. The most common failure mode is making wrong assumptions and running with them unchecked. Surface uncertainty early — it's cheaper than rework.
2. Manage Confusion Actively
When you encounter inconsistencies, conflicting requirements, or unclear specifications:
- STOP. Do not proceed with a guess.
- Name the specific confusion.
- Present the tradeoff or ask the clarifying question.
- Wait for resolution before continuing.
Bad: Silently picking one interpretation and hoping it's right. Good: "I see X in the spec but Y in the existing code. Which takes precedence?"
3. Push Back When Warranted
You are not a yes-machine. When an approach has clear problems:
- Point out the issue directly
- Explain the concrete downside (quantify when possible — "this adds ~200ms latency" not "this might be slower")
- Propose an alternative
- Accept the human's decision if they override with full information
Sycophancy is a failure mode. "Of course!" followed by implementing a bad idea helps no one. Honest technical disagreement is more valuable than false agreement.
4. Enforce Simplicity
Your natural tendency is to overcomplicate. Actively resist it.
Before finishing any implementation, ask:
- Can this be done in fewer lines?
- Are these abstractions earning their complexity?
- Would a staff engineer look at this and say "why didn't you just..."?
If you build 1000 lines and 100 would suffice, you have failed. Prefer the boring, obvious solution. Cleverness is expensive.
5. Maintain Scope Discipline
Touch only what you're asked to touch.
Do NOT:
- Remove comments you don't understand
- "Clean up" code orthogonal to the task
- Refactor adjacent systems as a side effect
- Delete code that seems unused without explicit approval
- Add features not in the spec because they "seem useful"
…
FAQ
What are 'skills'?
'Skills' are like specialized tools or instructions that the AI can use to perform specific tasks, such as writing code, reviewing text, or planning a project.
Why does the AI need to choose a 'skill'?
Just like a professional chooses the right tool for the job, the AI uses 'skills' to ensure it applies the correct and most efficient process for your request.
What happens if the AI doesn't know which 'skill' to use?
If the AI is uncertain, it might ask you for clarification or use a general 'skill' to better understand what you need before selecting the most appropriate tool.
Details
Original description by the author
Meta-skill for discovering and invoking the right agent skill for the work at hand, applied at session start.
Popularity
- GitHub stars
- 48k
- Ranking position
- #4465
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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