learn

A command that prints Peekaboo's complete guide for AI agents, including available tools, recommended working practices, and command-line options.

In plain words
What is it for?
Use it to display or capture the agent guide, tool definitions, usage examples, checklists, and the full list of CLI commands.
Why use it?
It provides the reference material another program or agent needs to understand Peekaboo's public interface.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/openclaw/peekaboo/learn
Clone the repo
git clone --depth 1 https://github.com/openclaw/Peekaboo
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 532 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00532
Opus 5 $0.00000 $0.00266
Sonnet 5 $0.00000 $0.00106
Haiku 4.5 $0.00000 $0.00053

Measured 2d ago against content hash 5684b5e16914, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

learn 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 2d 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.

docs/commands/learn.md · 38 lines

How it starts

The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.

peekaboo learn

peekaboo learn prints the canonical background-only public Agent guide. It stitches together the matching generated system prompt and Shell-free Agent tool registry, best-practice checklists, common workflows, and the full Commander signature table so other runtimes can stay in sync with the CLI release.

What it emits

  • System instructions straight from background-only AgentSystemPrompt.generate(), including communication rules and safety guidance.
  • Tool catalog grouped by category with each public Agent tool’s abstract, required/optional parameters, and JSON examples (if available). Shell is not a public Agent tool.
  • Best practices + quick reference: long-form guidance for automation patterns, then a condensed cheat sheet.
  • Commander section: a programmatic dump of every CLI command’s positional arguments, options, and flags (built by CommanderRegistryBuilder.buildCommandSummaries()).

Implementation notes

  • The command is intentionally text-only—--json is ignored—so downstream systems should capture stdout if they want to cache the content.
  • Everything runs on the main actor because it pulls the same background-only, policy-filtered toolset as a normal Agent session plus live Commander metadata; no parallel discovery catalog is involved.
  • Because it reuses the same builders the CLI uses at runtime, new commands/tools automatically show up here as soon as they land.
  • Background-only typing examples use a fresh exact non-dialog snapshot; app/PID/window-selector-only Agent typing is intentionally absent because policy refuses it.
  • When stdout is a rich TTY, output is rendered with Swiftdansi for ANSI color and table/box formatting; piped output stays plain Markdown for downstream tools.

Examples

# Save the full guide for another agent runtime
peekaboo learn > /tmp/peekaboo-guide.md

# Extract just the Commander signatures
peekaboo learn | awk '/^## Commander/,0'

Troubleshooting

  • Verify Screen Recording + Accessibility permissions (peekaboo permissions status).
  • Confirm your process with peekaboo app list, its exact window with peekaboo window list, and current UI with peekaboo see before rerunning.
  • Re-run with --json or --verbose to surface detailed errors.

Read the full file on GitHub · 38 lines

Changes

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.

  1. 2d ago First seen · 38 lines · 0 tokens per session scan A 5684b5e16914

Subscribe to this mod's changes

learn is a command published in the GitHub repository openclaw/Peekaboo (5,098 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 532 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.