skill-jmstar85-oh-my-githubcopilot-deep-dive · by Install
$ agentstack add skill-jmstar85-oh-my-githubcopilot-deep-dive ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-jmstar85-oh-my-githubcopilot-deep-dive) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Deep Dive
Orchestrates a 2-stage pipeline: first investigate WHY something happened (trace), then define WHAT to do about it (deep-interview). Trace findings feed into the interview via 3-point injection.
Pipeline
deep-dive → ralplan (consensus refinement) → omg-autopilot (execution)
When to Use
- User has a problem but doesn't know the root cause
- Bug investigation: "Something broke and I need to figure out why"
- Feature exploration: "I want to improve X but first need to understand it"
When NOT to Use
- Already know the root cause → use
/deep-interview - Clear specific request → execute directly
- Investigation only, no requirements → use
/trace
Phases
Phase 1: Initialize
- Parse problem, detect brownfield/greenfield
- Generate 3 trace lane hypotheses (code-path, config/env, measurement/artifact)
Phase 2: Lane Confirmation
Present hypotheses to user for confirmation (1 round).
Phase 3: Trace Execution
Run 3 parallel tracer lanes using @tracer agents:
- Each lane: evidence for, evidence against, critical unknown, discriminating probe
- Rebuttal round between top hypotheses
- Convergence detection
- Save to
.omg/specs/deep-dive-trace-{slug}.md
Phase 4: Interview with Trace Injection
Follow deep-interview protocol with 3 overrides:
- initial_idea enrichment: Include trace's most likely explanation
- codebase_context replacement: Use trace synthesis (skip re-exploration)
- question queue injection: Per-lane critical unknowns become first questions
Low-confidence trace: don't inject uncertain conclusion, use ALL unknowns as questions.
Phase 5: Execution Bridge
Same options as deep-interview: ralplan → omg-autopilot (recommended), omg-autopilot, ralph, team, or refine further.
Output
Spec saved to .omg/specs/deep-dive-{slug}.md with additional "Trace Findings" section.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: jmstar85
- Source: jmstar85/oh-my-githubcopilot
- License: MIT
- Homepage: https://www.linkedin.com/in/minsungjung/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.