Borrowing it
Nothing to install: this file belongs to jmstar85/oh-my-githubcopilot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jmstar85/oh-my-githubcopilot/main/.github/skills/deep-dive/SKILL.mdgit clone --depth 1 https://github.com/jmstar85/oh-my-githubcopilotWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jmstar85/oh-my-githubcopilot/deep-dive)<a href="https://agentmods.dev/skills/jmstar85/oh-my-githubcopilot/deep-dive"><img src="https://agentmods.dev/badge/skills/jmstar85/oh-my-githubcopilot/deep-dive/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jmstar85/oh-my-githubcopilot/deep-dive"><img src="https://agentmods.dev/badge/skills/jmstar85/oh-my-githubcopilot/deep-dive.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.00507 |
| Opus 5.5 | $0.00016 | $0.00203 |
| Sonnet 5.5 | $0.00008 | $0.00101 |
| Haiku 4.5 | $0.00004 | $0.00051 |
Grade A, and why
deep-dive scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
94% identical to deep-dive — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 55 lines · 40 tokens per session scan A dd58bf0db3cc
deep-dive is a skill published in the GitHub repository jmstar85/oh-my-githubcopilot (162 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 507 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to deep-dive, differing in 4 lines, and is treated as a copy.
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