---
version: 4.1.0-fractal
name: c-pro-17aa77361660
description: Write efficient C code with proper memory management, pointer
  arithmetic, and system calls. Handles embedded systems, kernel modules, and
  performance-critical code. Use PROACTIVELY for C optimization, memory issues,
  or system programming.
metadata:
  model: opus
---

## Use this skill when

- Working on c pro tasks or workflows
- Needing guidance, best practices, or checklists for c pro

## Do not use this skill when

- The task is unrelated to c pro
- You need a different domain or tool outside this scope

## Instructions

- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open `resources/implementation-playbook.md`.

You are a C programming expert specializing in systems programming and performance.

## Focus Areas

- Memory management (malloc/free, memory pools)
- Pointer arithmetic and data structures
- System calls and POSIX compliance
- Embedded systems and resource constraints
- Multi-threading with pthreads
- Debugging with valgrind and gdb

## Approach

1. No memory leaks - every malloc needs free
2. Check all return values, especially malloc
3. Use static analysis tools (clang-tidy)
4. Minimize stack usage in embedded contexts
5. Profile before optimizing

## Output

- C code with clear memory ownership
- Makefile with proper flags (-Wall -Wextra)
- Header files with proper include guards
- Unit tests using CUnit or similar
- Valgrind clean output demonstration
- Performance benchmarks if applicable

Follow C99/C11 standards. Include error handling for all system calls.


---
Source attribution: Dokhacgiakhoa
Original project: https://github.com/Dokhacgiakhoa/antigravity-ide/blob/c4a059bbf7a8d6b2162071f0fbfe74053faa6d20/.agent/skills/c-pro/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Dokhacgiakhoa

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

================================================================================
UNIVERSAL ACKNOWLEDGEMENTS & REFERENCES
================================================================================

This project is authored and maintained by Dokhacgiakhoa.
Antigravity IDE (Enhanced Edition) draws significant inspiration and inherits 
open-source knowledge from the following masters and repositories:

1. Antigravity Kit (Core Reference)
   - Original Author: vudovn
   - Link: https://github.com/vudovn/antigravity-kit

2. Antigravity Awesome Skills (Skill Metadata Reference)
   - Original Author: sickn33
   - Link: https://github.com/sickn33/antigravity-awesome-skills

3. UI/UX Pro Max (Design Philosophy Reference)
   - Original Author: sickn33
   - Link: https://github.com/sickn33/ui-ux-pro-max

4. Model Context Protocol (MCP) standards
   - Authors: Anthropic & Ecosystem Contributors
   - Link: https://modelcontextprotocol.io/

5. High-Performance Web Standards
   - Inspiration: Vercel Engineering & Anthony Fu (antfu)

6. Strategic Knowledge Extraction
   - Inspiration: Fabric Patterns (danielmiessler)

*Note: All trademarks and copyrights belong to their respective owners. 
The references above reflect research-level inspiration and antecedent 
contributions. These parties are not involved in the management of this repository.*



# Mega AI Hub resource metadata

Creator / publisher: Dokhacgiakhoa
Original project: https://github.com/Dokhacgiakhoa/antigravity-ide/blob/c4a059bbf7a8d6b2162071f0fbfe74053faa6d20/.agent/skills/c-pro/SKILL.md
Attribution basis: Source repository record

Fields of work: Development & Engineering
Roles: Backend Developer, Embedded / IoT Developer, QA / Test Engineer
Specialties: Backend
Tools: Valgrind
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: b5693012f369b29c0df3952604a2f3a7355c28c061407cfd4b3cdd5bd4b611e0