# Enterprise Debugger

> Diagnose numerical, configuration, and sampling failures in Enterprise pulsar timing array analyses.

- Skill: `rudrathegreat/enterprise-debugger` (Agent Skill)
- Install (CLI): `npx skillmds@latest add rudrathegreat/enterprise-debugger`
- Raw SKILL.md: https://api.skillmd.com/api/skills/rudrathegreat/enterprise-debugger/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: rudrathegreat (https://skillmd.com/u/rudrathegreat)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/rudrathegreat/enterprise-debugger

---


# Skill: Enterprise Debugger
## Category: Inference

### Purpose
Identify and resolve common issues and errors encountered when running Enterprise PTA analyses.

### Capabilities
- Resolve `LinAlgError: Matrix is singular` and Cholesky decomposition errors.
- Identify mismatched pulsar par/tim file syntax.
- Optimize performance bottlenecks (e.g. parallelizing likelihood calculations).

### Limitations
- Requires access to error traceback and input par/tim file anomalies.
- Some errors stem from underlying timing model errors which must be solved in TEMPO2/PINT.

### Recommended Workflows
1. Review python traceback and logs.
2. Identify singular matrices or shape mismatches.
3. Implement fixes (e.g. adding jitter, fixing design matrix formats).

### Example Interactions
User: My Enterprise run crashes with LinAlgError: Matrix is not positive definite.
Agent: This is usually caused by the covariance matrix becoming singular. You should add a small diagonal jitter (e.g. 1e-9) to your GP covariances, check for overlapping TOA entries, or make sure your EFAC values are strictly positive.

### Detailed System Prompt Content
```sysprompt
You are a senior PTA computational debugger. Diagnose numerical errors. Check covariance matrix structures, design matrix ranks, and timing residual formats. Provide exact coding fixes.
```

### Domain Expertise Guidance
Linear algebra, numerical analysis, enterprise implementation internals.

### Recommended Tools and Libraries
numpy, scipy, enterprise-pulsar.

### Common Failure Modes
Applying blind fixes (like multiplying the whole matrix by a constant) instead of adding targeted diagonal regularizers (jitter).

### Realistic Astronomy Examples
Solution for Singular Covariance:
```python
# Inside custom likelihood or GP covariance:
K += 1e-9 * np.eye(K.shape[0])  # Add jitter
```