list-learned-actions

list-learned-actions is a command for coding agents from Lykhoyda/rn-dev-agent. It costs 51 tokens per session (1,290 once invoked), scanned A, original, MIT.

A command that lists reusable knowledge saved from earlier testing sessions, including feedback notes, automated device flows, screen descriptions, and plugin commands. A learned action is a saved procedure or UI detail that can be reused later.

In plain words
What is it for?
Use it to search or review saved actions before creating new device-testing steps or running feature tests.
Why use it?
It prevents the agent from rediscovering the same device actions and project details from scratch.

Command

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the rn-dev-agent plugin — 11 skills, 16 commands, 5 agents, 6 hooks shipped together

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/lykhoyda/rn-dev-agent/list-learned-actions
Clone the repo
git clone --depth 1 https://github.com/Lykhoyda/rn-dev-agent

Or install rn-dev-agent, the plugin that ships this one along with the rest of its 11 skills, 16 commands, 5 agents, 6 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for list-learned-actions

README.md
[![agentmods](https://agentmods.dev/badge/commands/lykhoyda/rn-dev-agent/list-learned-actions.svg)](https://agentmods.dev/commands/lykhoyda/rn-dev-agent/list-learned-actions)
Your own site
<a href="https://agentmods.dev/commands/lykhoyda/rn-dev-agent/list-learned-actions"><img src="https://agentmods.dev/badge/commands/lykhoyda/rn-dev-agent/list-learned-actions.svg" alt="Measured on agentmods" height="20"></a>
Per session 51 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,290 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 $0.00051 $0.01290
Opus 5 $0.00026 $0.00645
Sonnet 5 $0.00010 $0.00258
Haiku 4.5 $0.00005 $0.00129

Measured 4d ago against content hash 5db40b6a6d2f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

list-learned-actions 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 4d 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.

packages/claude-plugin/commands/list-learned-actions.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

List learned actions matching: $ARGUMENTS (optional keyword filter; omit to list all)

Why this command exists

Past sessions accumulate two kinds of reusable knowledge that future sessions should look at BEFORE re-deriving anything from scratch:

  1. Feedback memories at ~/.claude/projects/<encoded-cwd>/memory/feedback_*.md
  2. Executable artifacts: .rn-agent/actions/*.yaml and *.yml, .rn-agent/skeleton.yaml

This command surfaces both lists in one place — and the underlying packages/rn-dev-agent-core/src/learned-actions.ts (compiled to packages/rn-dev-agent-core/dist/learned-actions.js) is the same script invoked programmatically by /rn-dev-agent:test-feature Step 0 and by the rn-tester / rn-debugger agents' artifact-scan steps. Keeping the discovery logic in one script means every consumer sees the same inventory.

Run

node "${CLAUDE_PLUGIN_ROOT}/rn-dev-agent-core/dist/learned-actions.js" \
  --workspace-root "$PWD" \
  --memory-cwd "$PWD" \
  ${ARGUMENTS:+--filter "$ARGUMENTS"}

The script auto-discovers:

  • The user's per-project auto-memory directory (Section A)
  • .rn-agent/actions/*.yaml and *.yml in the cwd, in <cwd>/test-app/, and in any <sibling>/test-app/ adjacent to the cwd (Section B)
  • .rn-agent/skeleton.yaml in the same locations (Section C)
  • Plugin commands (Section D — only populated when running inside the plugin repo)

It exits 0 when results found, 3 when nothing matches, 2 on bad flags.

Programmatic invocation

Other commands and agents can call the script directly to get JSON for decision-making. Always use --json from a programmatic caller — the human table format is not a stable contract.

RESULT=$(node "${CLAUDE_PLUGIN_ROOT}/rn-dev-agent-core/dist/learned-actions.js" \
  --json --section b --filter "task creation" --workspace-root "$PWD" --memory-cwd "$PWD")
echo "$RESULT" | jq '.sections.flows.items[0].path'

JSON shape (abridged):

{
  "cwd": "/Users/.../my-rn-app",
  "filter": "cart",
  "sections": {
    "memories": { "count": 0, "dir": "...", "items": [] },
    "flows": {
      "count": 1,
      "roots": ["..."],
      "items": [
        {
          "flow": "cart-add-item",
          "path": "/.../cart-add-item.yaml",
          "appId": "com.example.app",
          "purpose": "Add an item to the cart and verify the badge increments",
          "params": ["ITEM_ID", "QTY"],
          "replay": "display-only legacy command; execute through cdp_run_action"
        }
      ]
    },
    "skeletons": { "count": 1, "items": [...] },
    "commands": { "count": 16, "items": [...] }
  },
  "total": 18
}

Read the full file on GitHub · 124 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. 4d ago First seen · 124 lines · 51 tokens per session scan A 5db40b6a6d2f

Subscribe to this mod's changes

list-learned-actions is a command published in the GitHub repository Lykhoyda/rn-dev-agent (11 stars, last pushed yesterday), licensed MIT. It adds 51 tokens to every session and 1,290 once invoked, about $0.0003 per session on Opus 5. 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.