Opencode Coding
by Roy Yuen
Enforce senior-level coding standards with a focus on verification, minimal diffs, and evidence-based bug fixing.
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You say
Audit the authentication service for timing attack vulnerabilities. If found, implement the most surgical fix possible and verify it against existing tests.
Your agent does
Verified: Ran pytest tests/auth/ (3 passed).
Inferred: DB connection pool handles the retry logic based on line 42 config.
Unknown: Scaling behavior under 10k concurrent reqs.
Change: Modified auth_service.py L89 to use safe_compare to prevent timing attacks. Smallest safe fix.
What you get
About this skill
What it does
Opencode Coding is a high-performance skill designed to enforce senior-engineer coding standards across any AI model. It moves beyond "prompt-and-hope" coding by mandating a rigorous technical workflow: verify first, implement the narrowest defensible change, and prove success through execution rather than inspection.
Why use this skill
Standard LLM coding often suffers from "hallucinated confidence" and bloated, speculative refactors. This skill solves that by forcing the agent to adopt a Codex-grade standard. It is better than simple prompting because it embeds a systematic engineering contract: every change must be localized, every bug must be reproduced, and every completion must state exactly what was verified and what remains unknown. It turns your agent into an engineer that values stability and evidence over cleverness.
Key Features
- Evidence-Based Debugging: Identifies root causes and reproduces failures before proposing fixes.
- Minimal Impact Diffs: Prioritizes the smallest safe change to preserve project patterns and reduce regression risk.
- Verification-First Workflow: mandates running targeted tests, linters, or manual validations before reporting success.
- Standardized Reporting: Every output includes a "Response Contract" detailing what was Verified, Inferred, and Unknown.
Supported Use Cases
This skill is framework-agnostic and works across any tech stack. Use it for complex feature implementation, surgical bug fixing, safe refactoring of legacy modules, and rigorous PR reviews where functional correctness is the priority.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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1033+ total installs · 111 skills on Agensi
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