autonomous-coding-loop
MANDATORY CORE SKILL: Enforces the Autonomous Coding & Self-Correction Loop for Antigravity in every session.
Skill by nguyenhungtran18
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/nguyenhungtran18-autonomous-coding-loop
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: testing, writing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/autonomous-coding-loop
What's inside
- Skill name
autonomous-coding-loop- Description
- MANDATORY CORE SKILL: Enforces the Autonomous Coding & Self-Correction Loop for Antigravity in every session. Activate this skill whenever writing, modifying, refactoring, or debugging code, implementing features, or fixing bugs across any programming language. It mandates rigorous specification analysis, test-first synthesis, sandboxed execution, failure taxonomy classification, and iterative zero-regression self-correction.
- License
- MIT
- Instructions
- 83 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (3)
- SKILL.md
- loop_specification.md · references/
- verify_loop.py · scripts/
SKILL.md (first lines)
# Autonomous Coding & Self-Correction Loop (Antigravity Core Workflow)
This skill mandates and guides the **Autonomous Coding & Self-Correction Loop** for Antigravity in all coding and debugging sessions.
---
## 1. Golden Invariant: Never Deliver Unverified Code
Antigravity must **NEVER** guess, assume, or deliver code without proving correctness through the 6-phase closed-loop cycle:
```mermaid
flowchart LR
A[Phase 1: Spec & Invariants] --> B[Phase 2: Test Synthesis]
B --> C[Phase 3: Code Actuation]
C --> D[Phase 4: Multi-Tier Verification]
D --> E{All Tests Pass?}
E -- Yes --> F[Phase 6: Convergence & Proof]
E -- No --> G[Phase 5: Diagnostic & Repair]
G --> C
```
---
## 2. Mandatory 6-Phase Execution Protocol
Whenever user tasks involve writing, editing, or fixing code, you **MUST** execute the following phases:
### Phase 1: Problem Decomposition & Invariant Grounding
1. Identify functional requirements, non-functional performance targets, and boundary constraints.
2. Establish explicit **Invariant Rules** $\mathcal{I}$ that must remain invariant throughout execution.
3. If the task is non-trivial, activate Planning Mode and construct [`implementation_plan.md`](./references/loop_specification.md).
### Phase 2: Multi-Tier Verification & Test Bench Synthesis (Test-First / CEGIS)
Synthesize verification probes *before* or *in conjunction with* code changes:
- **Level 1: Static AST & Typing**: Type hints, linters, import validation.
- **Level 2: Core Invariant Tests**: Functional happy paths and mathematical correctness.
- **Level 3: Boundary & Edge Tests**: $0, -1, \text{None}$, empty collections, max buffer sizes.
- **Level 4: Concurrency & Safety Probes**: Thread synchronization, race conditions, memory leaks.
- **Level 5: Rollback & Transactional Invariants**: Fault-injection and atomic state resets.
### Phase 3: High-Precision Code Actuation
- Use targeted modification tools: [`replace_file_content`](#) or [`multi_replace_file_content`](#) for surgical edits.
- Maintain comment integrity and adhere to existing codebase architectural idioms.
- Avoid massive full-file rewrites unless creating brand new modules.
### Phase 4: Sandboxed Execution & Telemetry Capture
- Run unit test suites, linters, and verification scripts via `run_command`.
- Intercept and isolate standard outputs, errors, exit codes, and structured tracebacks.
### Phase 5: Seven-Tier Failure Classification & Anti-Regression Repair
If any verification probe fails, classify the failure using the **Failure Taxonomy Matrix**:
| Category | Diagnostic Signal | Actionable Repair Strategy |
| :--- | :--- | :--- |
| **`SYNTAX_ERROR`** | `SyntaxError`, indentation, token mismatch | Re-parse AST, fix syntax, balance delimiters |
| **`TYPE_ERROR`** | `TypeError`, `AttributeError`, `NameError` | Inspect interfaces, add type narrowing & guards |
| **`RUNTIME_ASSERTION`** | `AssertionError`, state mismatch | Trace state transitions, audit return transformations |
| **`EDGE_CASE_BREACH`** | Boundary condition failures | Add defensive clauses for zero/null/empty/negative inputs |
| **`TIMEOUT_INFINITE_LOOP`** | Process hang, deadlock | Add loop invariants, recursion limits, non-blocking locks |
| **`SEMANTIC_LOGIC_ERROR`** | Incorrect output despite valid syntax | Step through algorithm invariants and formula logic |
| **`ENVIRONMENT_OR_IO`** | Missing packages, permissions | Check environment, install dependencies, resolve paths |
#### Anti-Regression Invariant:
- Maintain a checkpoint of the best passing state.
- After applying each patch, run the entire test suite.
- If a patch introduces a regression (fails a previously passing test), immediately revert the patch and formulate an alternative hypothesis.
### Phase 6: Formal Convergence & Walkthrough Synthesis
- Convergence is achieved when **100% of test cases pass with 0 regressions**.
- Document changes, validation results, and telemetry in [`walkthrough.md`](./references/loop_specification.md).
---
## 3. Quick Reference Scripts & Tools
- Run loop verification harness:
```powershell
python .agents/skills/autonomous-coding-loop/scripts/verify_loop.py
```
- Detailed mathematical specification:
[references/loop_specification.md](references/loop_specification.md)From nguyenhungtran18/skill-and-tool-tracker, MIT.
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Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Aug 31, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
autonomous-coding-loop skill. Agent Mart. https://agentmart.dev/skills/nguyenhungtran18-autonomous-coding-loop (last updated 2026-10-24)