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This skill should be used when solving hard questions, complex architectural problems, or debugging issues that benefit from GPT-5 Pro or GPT-5.1 thinking models with large file context. Use when standard Claude analysis needs deeper reasoning or extended context windows.

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Updated 2/8/2026

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SKILL.md

Ask Oracle Skill

Leverage the Oracle CLI to tap into GPT-5 Pro / GPT-5.1 for hard problems that benefit from extended reasoning and large code context.

When to Use

Invoke this skill when:

  • Problem requires deep reasoning beyond single-response analysis
  • Debugging complex issues across large codebases (100k+ lines)
  • Architectural decisions need careful evaluation with full context
  • Performance optimization requires comprehensive code analysis
  • Security reviews need thorough codebase inspection
  • Standard Claude analysis feels insufficient
  • Problem statement includes "hard", "complex", "architectural", "across the codebase"

Core Capabilities

The Oracle CLI (bunx @steipete/oracle) provides:

  • GPT-5 Pro (default): Advanced reasoning for difficult problems
  • GPT-5.1: Experimental model with different reasoning approach
  • File context: Attach entire directories/files (up to ~196k tokens)
  • Sessions: Long-running background sessions with resume capability
  • Token reporting: Inspect file token costs before calling API

Workflow

Step 1: Assess the Problem

Determine if oracle is needed:

  • Is the problem genuinely hard/complex?
  • Does it benefit from seeing more code context?
  • Would standard Claude response be insufficient?

If yes, proceed. If it's a simple question, just answer directly.

Step 2: Gather Relevant Context

Identify files/directories to attach using --file:

  • Architecture files (README, package.json, main entry points)
  • Relevant source directories (src/, lib/, etc.)
  • Configuration files (tsconfig, build config, etc.)
  • Tests if they illuminate the problem
  • Error logs or reproduction scripts

Exclude:

  • Node modules (node_modules/)
  • Build artifacts (dist/, build/)
  • Large vendored code
  • Binary files

Step 3: Choose Model and Preview

For most hard problems, use default GPT-5 Pro:

bunx @steipete/oracle --prompt "Your question here" --file src/ docs/ --preview

For experimental approach, try GPT-5.1:

bunx @steipete/oracle --prompt "Your question here" --file src/ docs/ --model gpt-5.1 --preview

Always preview first to check token usage:

bunx @steipete/oracle --prompt "Question" --file src/ --files-report --preview

Step 4: Review Token Report

When using --files-report, output shows token costs per file:

Files Report:
  src/components/form.tsx: 3,245 tokens
  src/utils/helpers.ts: 1,023 tokens
  src/api/client.ts: 2,156 tokens
  Total: 6,424 tokens (under ~196k budget)

If total exceeds budget:

  • Remove less relevant files
  • Focus on key directories only
  • Exclude verbose files (logs, generated code)
  • Ask a more specific question to reduce needed context

Step 5: Execute Query

Once satisfied with preview, run without --preview to actually call the model:

bunx @steipete/oracle --prompt "Your question here" --file src/ docs/ --slug "my-problem"

Oracle runs as background session - terminal can close without losing work.

Step 6: Monitor or Resume Session

To attach to running session:

bunx @steipete/oracle session <session-id>

To list recent sessions (last 24h):

bunx @steipete/oracle status

To specify custom session slug (easier to remember):

bunx @steipete/oracle --slug "auth-flow-design" --prompt "..." --file src/

Later, attach via slug:

bunx @steipete/oracle session auth-flow-design

Key Options

OptionPurposeExample
--promptThe question to ask--prompt "Why does this auth flow fail?"
--fileAttach files/dirs (repeatable)--file src/ docs/ --file error.log
--slugHuman-memorable session name--slug "perf-optimization-review"
--modelWhich model to use--model gpt-5.1 (default: gpt-5-pro)
--engineapi or browser--engine api (default: auto-detect)
--files-reportShow token per fileHelps optimize context
--previewValidate without calling APITest before spending tokens
--dry-runShow token estimates onlySafer than preview
--heartbeatProgress updates (seconds)--heartbeat 30 (default)

Common Patterns

Hard Debugging Question

bunx @steipete/oracle \
  --prompt "Why does this auth flow fail on mobile? Trace through the code flow." \
  --file src/auth/ src/api/ docs/AUTH.md \
  --slug "mobile-auth-debug" \
  --files-report \
  --preview

Architectural Review

bunx @steipete/oracle \
  --prompt "Review the state management architecture. What are risks and improvements?" \
  --file src/store/ src/components/ README.md \
  --slug "state-arch-review"

Performance Analysis

bunx @steipete/oracle \
  --prompt "Where are the performance bottlenecks in this renderer?" \
  --file src/renderer/ performance-logs.txt \
  --slug "renderer-perf" \
  --files-report

Security Review

bunx @steipete/oracle \
  --prompt "Identify security concerns in the authentication and API layers." \
  --file src/auth/ src/api/ src/middleware/ \
  --slug "security-audit"

Best Practices

  1. Always preview first: Use --preview or --files-report to inspect tokens before committing budget
  2. Use memorable slugs: Makes it easier to resume and reference later
  3. Ask focused questions: More specific = better reasoning. Avoid "review everything"
  4. Provide context in prompt: "We're building X in domain Y, and problem is Z"
  5. Attach key architecture docs: READMEs, design docs help oracle understand intent
  6. Keep files under 1MB: Automatic rejection, so plan accordingly
  7. Use browser engine for API-less runs: Falls back to browser if no OPENAI_API_KEY set
  8. Check token budget: ~196k tokens max per request (files + prompt)

Examples

Example 1: Complex Bug Investigation

bunx @steipete/oracle \
  --prompt "This form submission intermittently fails with 'network timeout'. Walk through the request/response cycle, check timeout configs, and trace where it might stall." \
  --file src/components/Form.tsx src/api/client.ts src/hooks/useSubmit.ts \
  --files-report \
  --preview

Example 2: Design Review with Alternatives

bunx @steipete/oracle \
  --prompt "We're using redux for state management in a 50k LOC codebase. Is this still optimal? What are 2-3 alternatives worth considering?" \
  --file src/store/ docs/ARCHITECTURE.md package.json \
  --slug "state-mgmt-design"

Example 3: Resume Previous Session

# Earlier you ran:
bunx @steipete/oracle --prompt "..." --slug "my-problem"

# Now attach to it:
bunx @steipete/oracle session my-problem

Edge Cases & Troubleshooting

Files too large (>1MB):

  • Exclude vendored code, logs, or split context
  • Focus on key files only

Token budget exceeded (~196k):

  • Show --files-report to see cost per file
  • Reduce number of files or directories
  • Ask more specific question to require less context

Session doesn't exist:

  • Check spelling of slug/ID
  • Run bunx @steipete/oracle status to list recent sessions
  • Create new session if needed

OPENAI_API_KEY not set:

  • Oracle falls back to browser engine
  • Use --engine browser explicitly if preferred
  • Set API key to use API engine for background sessions

Preview shows too many tokens:

  • Exclude directories with large generated files
  • Keep only most relevant source files
  • Split into multiple focused queries

Implementation Notes

  • Oracle CLI is installed via bunx @steipete/oracle (no local install needed)
  • Sessions run in background; terminal close doesn't stop them
  • Responses stream via heartbeat (default 30s intervals)
  • Use --slug for easier session management in team workflows
  • Token budget is per-request (~196k combined), not per session

When NOT to Use Oracle

  • Simple questions answerable in seconds
  • Trivial code changes or minor bugs
  • Context < 10k tokens
  • Answers need immediate turnaround (background sessions take time)
  • No code context needed (use standard Claude instead)

Install

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Requires askill CLI v1.0+

AI Quality Score

96/100Analyzed 2/10/2026

An exceptionally well-documented skill for using the Oracle CLI to leverage advanced LLMs for complex tasks. It includes clear triggers, detailed workflows, command references, and troubleshooting.

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Licenseunknown
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Updated2/8/2026
Publisheriamladi

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apici-cdgithub-actionsllmpromptingsecuritytesting