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Prompts & LLMs48k · #4303

system-prompt-lookup

Checks an AI agent's exact instructions by consulting a historical archive. This ensures the agent follows the correct rules. Useful before trusting the agent's actions.

What it does

This tool checks what an AI program was actually told in its instructions (called a 'system prompt') and what tools it can use. It does this by looking at a historical archive of instructions from AI programs that have already been released, instead of trying to remember.

When to use it

  • ✓When someone asks for an AI program's instructions.
  • ✓Before stating what an AI program was instructed to do.
  • ✓When comparing different AI programs, like the size of their instructions or number of tools.

Example of what to ask your AI

“Check the instructions for the 'Claude-Code' program.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/system-prompt-lookup/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/system-prompt-lookup/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool searches a historical archive for the system prompts and tool schemas of released AI programs. It reads the files directly to ensure the information is exact and not an inaccurate recollection.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill system-prompt-lookup

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/system-prompt-lookup/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Checking what an agent was actually told

Overview

OrcaPromptVault is a dated archive of the system prompts and tool-call schemas that shipped AI products send — one directory per product, schemas stored as JSON. Each artifact records how it was obtained: captured off the wire while the harness ran unmodified, or reported by the vendor.

This skill is the judgement layer over that archive. It exists because models, including the one reading this, will happily produce a confident paraphrase of a product's system prompt that is a reconstruction rather than a quotation. The archive is a primary source; your recollection of it is not.

Read-only. Nothing here installs, runs, or mutates anything; the only external access is fetching public files from github.com.

When to Use This Skill

  • Use when the user asks what a product's system prompt says, or quotes one and asks whether it is real.
  • Use when you are about to state that some agent is instructed to do something — check first.
  • Use when comparing products: how large a prompt is, how many tools it ships, how it phrases a refusal or a safety rule.
  • Use when someone shows you an extracted or leaked prompt and wants it verified.
  • Use when writing a harness and you want to see how shipped ones solve the same problem.

Do not use it to conclude that a product behaves a certain way today. Every artifact is a dated snapshot of one version on one day.

How It Works

Step 1: Find the product directory

Top-level directories are named after the product: Claude-Code/, Cursor/, Codex/, Cline/, Devin/, Windsurf/, Goose/, Crush/, OpenClaw/, Manus/, Perplexity/ and others. Each has a README.md listing its files with the model, the mode, the character count and the tool count.

# What products exist
curl -s https://api.github.com/repos/Continuum-AI-Corp/OrcaPromptVault/contents | grep '"name"'

# What is inside one of them
curl -s https://api.github.com/repos/Continuum-AI-Corp/OrcaPromptVault/contents/Claude-Code | grep '"name"'

Step 2: Read the file, not a summary of it

File names carry the facts: <product>-<model>-system-prompt-<date>.md for the prompt, <product>-<model>-tools.json for the schema that travelled with it. A -print- segment marks the non-interactive mode rather than the interactive one.

BASE=https://raw.githubusercontent.com/Continuum-AI-Corp/OrcaPromptVault/main
curl -s "$BASE/Claude-Code/claude-code-opus-5-system-prompt-2026-09-03.md" | head -40
curl -s "$BASE/Claude-Code/claude-code-opus-5-tools.json" | grep -o '"name": *"[^"]*"'

Quote from what you fetched. If you did not fetch it, say so rather than reconstructing it.

Step 3: Check the provenance label before relying on it

docs/CAPTURES.md lists every artifact that was pulled off the wire, with the date, the character count, and the command that reproduces it. Anything absent from that table came from a vendor publication or an upstream collection — still useful, but it is the vendor's account of its own prompt, which is a different kind of evidence.

curl -s "$BASE/docs/CAPTURES.md" | grep -i "claude code"

Say which kind you are citing. Captured on a given date and published by the vendor are not interchangeable claims.

Step 4: Diff, do not eyeball

Two artifacts of the same product differ for a reason worth reporting.

curl -s "$BASE/Claude-Code/claude-code-fable-5.1-system-prompt-2026-09-02.md" -o /tmp/a.md
curl -s "$BASE/Claude-Code/claude-code-fable-5.1-print-system-prompt-2026-09-02.md" -o /tmp/b.md
diff /tmp/a.md /tmp/b.md | head -60

Same model, same day, interactive versus headless: the identity line itself changes and the tool list shrinks. A claim about the prompt of a product that ships several modes is under-specified.

Examples

Example 1: The user quotes a prompt and asks whether it is genuine

User: Is this really in Claude Code's system prompt? "You are a Claude agent, built on
Anthropic's Claude Agent SDK."

Fetch both modes for that model, grep for the line, and answer with the mode it belongs to — here the headless/SDK capture rather than the interactive one. Give the file name and its capture date, not a summary.

Example 2: Comparing tool surfaces across products

BASE=https://raw.githubusercontent.com/Continuum-AI-Corp/OrcaPromptVault/main

…
FAQ

What is a 'system prompt'?

It's the initial set of instructions an AI program receives to know how to behave and what to do.

What are 'tool schemas'?

These are descriptions of the tools or functions an AI program can use to perform tasks.

Does this tool change an AI program's instructions?

No, this tool only reads information from a historical archive. It does not install, run, or modify anything.

Details

Original description by the author

Checks what a shipped AI product's system prompt and tool schema actually say, by reading a dated archive of captured prompts instead of recalling them. Use before asserting or accepting any claim about an agent's instructions.

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#4303
License
MIT
Updated
10/15/2026

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