Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Use the @steipete/oracle CLI to bundle a prompt plus the right files and get a second-model review (API or browser) for debugging, refactors, design checks, or cross-validation.
Use the @steipete/oracle CLI to bundle a prompt plus the right files and get a second-model review (API or browser) for debugging, refactors, design checks, or cross-validation.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Oracle bundles your prompt + selected files into one “one-shot” request so another model can answer with real repo context (API or browser automation). Treat outputs as advisory: verify against the codebase + tests.
Default workflow here: --engine browser with GPT‑5.2 Pro in ChatGPT. This is the “human in the loop” path: it can take ~10 minutes to ~1 hour; expect a stored session you can reattach to. Recommended defaults: Engine: browser (--engine browser) Model: GPT‑5.2 Pro (either --model gpt-5.2-pro or a ChatGPT picker label like --model "5.2 Pro") Attachments: directories/globs + excludes; avoid secrets.
Pick a tight file set (fewest files that still contain the truth). Preview what you’re about to send (--dry-run + --files-report when needed). Run in browser mode for the usual GPT‑5.2 Pro ChatGPT workflow; use API only when you explicitly want it. If the run detaches/timeouts: reattach to the stored session (don’t re-run).
Show help (once/session): npx -y @steipete/oracle --help Preview (no tokens): npx -y @steipete/oracle --dry-run summary -p "<task>" --file "src/**" --file "!**/*.test.*" npx -y @steipete/oracle --dry-run full -p "<task>" --file "src/**" Token/cost sanity: npx -y @steipete/oracle --dry-run summary --files-report -p "<task>" --file "src/**" Browser run (main path; long-running is normal): npx -y @steipete/oracle --engine browser --model gpt-5.2-pro -p "<task>" --file "src/**" Manual paste fallback (assemble bundle, copy to clipboard): npx -y @steipete/oracle --render --copy -p "<task>" --file "src/**" Note: --copy is a hidden alias for --copy-markdown.
--file accepts files, directories, and globs. You can pass it multiple times; entries can be comma-separated. Include: --file "src/**" (directory glob) --file src/index.ts (literal file) --file docs --file README.md (literal directory + file) Exclude (prefix with !): --file "src/**" --file "!src/**/*.test.ts" --file "!**/*.snap" Defaults (important behavior from the implementation): Default-ignored dirs: node_modules, dist, coverage, .git, .turbo, .next, build, tmp (skipped unless you explicitly pass them as literal dirs/files). Honors .gitignore when expanding globs. Does not follow symlinks (glob expansion uses followSymbolicLinks: false). Dotfiles are filtered unless you explicitly opt in with a pattern that includes a dot-segment (e.g. --file ".github/**"). Hard cap: files > 1 MB are rejected (split files or narrow the match).
Target: keep total input under ~196k tokens. Use --files-report (and/or --dry-run json) to spot the token hogs before spending. If you need hidden/advanced knobs: npx -y @steipete/oracle --help --verbose.
Auto-pick: uses api when OPENAI_API_KEY is set, otherwise browser. Browser engine supports GPT + Gemini only; use --engine api for Claude/Grok/Codex or multi-model runs. API runs require explicit user consent before starting because they incur usage costs. Browser attachments: --browser-attachments auto|never|always (auto pastes inline up to ~60k chars then uploads). Remote browser host (signed-in machine runs automation): Host: oracle serve --host 0.0.0.0 --port 9473 --token <secret> Client: oracle --engine browser --remote-host <host:port> --remote-token <secret> -p "<task>" --file "src/**"
Stored under ~/.oracle/sessions (override with ORACLE_HOME_DIR). Runs may detach or take a long time (browser + GPT‑5.2 Pro often does). If the CLI times out: don’t re-run; reattach. List: oracle status --hours 72 Attach: oracle session <id> --render Use --slug "<3-5 words>" to keep session IDs readable. Duplicate prompt guard exists; use --force only when you truly want a fresh run.
Oracle starts with zero project knowledge. Assume the model cannot infer your stack, build tooling, conventions, or “obvious” paths. Include: Project briefing (stack + build/test commands + platform constraints). “Where things live” (key directories, entrypoints, config files, dependency boundaries). Exact question + what you tried + the error text (verbatim). Constraints (“don’t change X”, “must keep public API”, “perf budget”, etc). Desired output (“return patch plan + tests”, “list risky assumptions”, “give 3 options with tradeoffs”).
When you know this will be a long investigation, write a prompt that can stand alone later: Top: 6–30 sentence project briefing + current goal. Middle: concrete repro steps + exact errors + what you already tried. Bottom: attach all context files needed so a fresh model can fully understand (entrypoints, configs, key modules, docs). If you need to reproduce the same context later, re-run with the same prompt + --file … set (Oracle runs are one-shot; the model doesn’t remember prior runs).
Don’t attach secrets by default (.env, key files, auth tokens). Redact aggressively; share only what’s required. Prefer “just enough context”: fewer files + better prompt beats whole-repo dumps.
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.