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Oracle

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steipete
oracle

Oracle second-model review: bundle prompts/files, debug, refactor, design.

Overview

Publishersteipete
Repositoryagent-scripts
Skill nameoracle
Stars
6.6K
Forks
547
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by steipete on GitHub. Read the source before you install it.

Installation

Install the Oracle AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/steipete/agent-scripts.git /tmp/agent-scripts
mkdir -p .claude/skills
cp -r /tmp/agent-scripts/skills/oracle .claude/skills/oracle
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Oracle in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Oracle on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Oracle is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Oracle (CLI) — best use

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.

Main use case (browser, GPT‑5.5 Pro)

Default workflow here: --engine browser with GPT‑5.5 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‑5.5 Pro (either --model gpt-5.5-pro or a ChatGPT picker label like --model "5.5 Pro")
  • Attachments: directories/globs + excludes; avoid secrets.

Golden path (fast + reliable)

  1. Pick a tight file set (fewest files that still contain the truth).
  2. Preview what you’re about to send (--dry-run + --files-report when needed).
  3. Run in browser mode for the usual GPT‑5.5 Pro ChatGPT workflow; use API only when you explicitly want it.
  4. If the run detaches/timeouts: reattach to the stored session (don’t re-run).

Commands (preferred)

  • 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/**"
  • Startup/perf trace:

    • npx -y @steipete/oracle --perf-trace --perf-trace-path /tmp/oracle-perf.json --dry-run summary -p "<task>" --file "src/**"
    • Use when CLI startup or time-to-first-output feels slow; inspect first-output and exit.
  • Browser run (main path; long-running is normal):

    • npx -y @steipete/oracle --engine browser --model gpt-5.5-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.

Attaching files (--file)

--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/**").
    • Default cap: files > 1 MB are rejected unless you raise ORACLE_MAX_FILE_SIZE_BYTES or maxFileSizeBytes in ~/.oracle/config.json.

Budget + observability

  • Target: keep total input under ~196k tokens.
  • Use --files-report (and/or --dry-run json) to spot the token hogs before spending.
  • Use --perf-trace / ORACLE_PERF_TRACE=1 for startup and first-output timing. Traces redact prompts, tokens, keys, cookies, and inline cookie payloads; detached API children write a session-suffixed sidecar trace.
  • If you need hidden/advanced knobs: npx -y @steipete/oracle --help --verbose.

Engines (API vs browser)

  • 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).
    • Add --browser-bundle-files --browser-bundle-format zip to upload many text files as one ZIP while preserving file names.
  • 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/**"

API preflight

  • API runs require explicit user consent and cost money.
  • Before API runs, check provider readiness without printing secrets:
    • oracle doctor --providers --models gpt-5.4,claude-4.6-sonnet,gemini-3-pro
    • oracle --preflight --models gpt-5.4,gemini-3-pro
    • oracle --route --model gpt-5.4
  • If the user wants first-party OpenAI, pass --provider openai or --no-azure. This prevents exported Azure env/config from hijacking the route:
    • oracle --provider openai --engine api --model gpt-5.5-pro ...
  • For advisory multi-model panels where partial success is useful, use --allow-partial --write-output <path> so successful model files and the <stem>.oracle.json manifest are easy to recover:
    • oracle --models gpt-5.4,claude-4.6-sonnet,gemini-3-pro --allow-partial --write-output /tmp/panel.md -p "<task>"
  • --timeout 10m is the normal user-facing API deadline; Oracle derives the HTTP transport timeout unless --http-timeout is explicitly set.
  • If the exported OPENAI_API_KEY is invalid and the user wants their personal OpenAI key, use $one-password in one persistent tmux session. Known item: API Key - OpenAI - Personal, field api_key. Inject only into the single Oracle command; never print the key:
    • OPENAI_API_KEY="$(op item get 'API Key - OpenAI - Personal' --account my.1password.com --fields label=api_key --reveal)" oracle --provider openai --engine api --model gpt-5.5-pro ...
  • For debugging Oracle itself, prefer the local checkout after pulling ~/Projects/oracle:
    • pnpm -C ~/Projects/oracle run build
    • node ~/Projects/oracle/dist/scripts/run-cli.js ...

Sessions + slugs (don’t lose work)

  • Stored under ~/.oracle/sessions (override with ORACLE_HOME_DIR).
  • Browser runs save durable files under ~/.oracle/sessions/<id>/artifacts/, including transcript.md, Deep Research reports, and downloaded ChatGPT-generated images when available.
  • Runs may detach or take a long time (browser/API + GPT‑5.5 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.
  • CLI guardrails: root runs without a prompt exit nonzero; --dry-run conflicts with --render / --render-markdown; Ctrl-C exits foreground API runs with code 130 while browser cleanup/reattach still runs.

Prompt template (high signal)

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”).

“Exhaustive prompt” pattern (for later restoration)

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).

Safety

  • 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.

Frequently asked questions

What does the Oracle AI skill do?

Oracle second-model review: bundle prompts/files, debug, refactor, design.

Why use Oracle on TypingMind?

Because you install it once and use it with any model. Oracle is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Oracle in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/steipete/agent-scripts/tree/main/skills/oracle. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Oracle?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Oracle?

As many as you like. As long as a model supports skills, you can use Oracle with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Oracle AI skill free?

Yes. It is published on GitHub by steipete under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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