coding-core

Guides bounded code patches, debugging, and review with explicit verification and claim boundaries.

Updated May 22, 2026
One-click install
npx skills add https://github.com/handaeho/Harness_Engineering --skill coding-core-handaeho
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: coding-core
Source: https://github.com/handaeho/Harness_Engineering/tree/main/prompt-stack/_candidates/v36_candidate/codex/skills/coding-core
Command: npx skills add https://github.com/handaeho/Harness_Engineering --skill coding-core-handaeho

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? AI coding agents often overstate results, widen scope into unrelated refactors, or claim fixes without running validation. This Skill enforces bounded patch discipline, honest verification language, and explicit separation between checked and unverified behavior for coding tasks. ## Core Features & Use Cases - Bounded Patch Discipline: Isolates the smallest responsible unit, patches narrowly, and blocks repo-wide rewrites disguised as fixes. - Structured Debugging Loop: Applies a symptom-to-cause-to-fix-to-verification workflow with ranked candidate causes and reversible probes first. - Verification Honesty: Separates what changed, what was checked, and what remains unverified, prohibiting words like "fixed" or "done" without evidence. - Use Case: When asked to fix a failing function, the agent reads only the active slice, proposes a minimal diff, runs the strongest available local check, and reports integration risks that still need human review. ## Quick Start Ask the agent to debug and patch a specific failing function while keeping the change scope minimal and reporting exactly what was verified.

Frequently Asked Questions about coding-core

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I get an AI agent to make minimal code changes?

Use a bounded patch workflow that isolates the smallest responsible unit before editing. The agent reads only the active slice, patches narrowly, preserves untouched files, and states the change scope explicitly instead of widening into cleanup.

How should an AI coding agent report verification results?

The agent must separate what changed, what was checked, and what remains unverified. It avoids words like fixed or done unless the solved condition is justified, and names the safest next validation step.

What is diff-first debugging for coding agents?

It is a structured loop of observed symptom, candidate causes, most likely cause, fix strategy, then verification. Causes are ranked by evidence fit, reversible probes run before irreversible changes, and weak evidence is stated openly.

When should a coding agent switch to propose-only mode?

Switch to propose-only when the change involves broad refactors, shared interface changes, data migration, destructive file operations, deployment behavior, or secrets handling. The plan is presented for human review before execution.

Can this approach handle harness runner and telemetry code changes?

Yes, it includes a harness-aware mode that keeps runner, sandbox, trace, and telemetry contract ownership explicit. It preserves executed-versus-designed status and prefers baseline recovery before new feature work when the substrate is broken.

What are the limitations of a bounded patch workflow?

It is not suited for document-grounded research, architecture comparison, or release gate evaluation tasks. When the real answer is a broad redesign, the agent must say so explicitly rather than sneaking it into a local patch.