Official agent skill

Nemo Rl Session Memory

by NVIDIA in NVIDIA/skills

Manage durable working-session memory for coding agents. An agent skill from NVIDIA/skills.

OfficialApache-2.0Auto-check passedAgent Workflows

Install Nemo Rl Session Memory

skills CLI
$ npx skills add NVIDIA/skills --skill nemo-rl-session-memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install NVIDIA/skills nemo-rl-session-memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/nemo-rl-session-memory .claude/skills/nemo-rl-session-memory && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
nemo-rl-session-memory
GitHub stars
3.5k
Token cost
~1.4k tokens
SKILL.md length
465 words
Files
5
Skills in repo
380
Repo updated
First seen
Licence
Apache-2.0

At a glance

Manage durable working-session memory for coding agents. An agent skill from NVIDIA/skills.

  • Works in 4 steps: Check for existing session directories → If the user is resuming work, read the… → If no relevant session exists, create a… → …
  • A user asks to preserve
  • SKILL.md covers When To Use, Session Directory, Start Or Resume and Checkpoint Rhythm, plus 3 more sections
  • Calls git

What it does

Nemo Rl Session Memory is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Manage durable working-session memory for coding agents. Use when a user asks to preserve or recover agent context across disconnects, VS Code restarts, long-running work, handoffs, or any session where important state should be written periodically under the repo's session directory. Do NOT use for: simple questions, short tasks, one-off commands, linting, or code review.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files (for example `BENCHMARK.md`, `evals/evals.json` and `skill-card.md`).

It sits in Agent Workflows, covering Agent memory, Session handoff and Linting and formatting. It works with Visual Studio Code. The repository describes itself as: Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end. The licence is Apache-2.0.

When your agent uses it

  • A user asks to preserve
  • Recover agent context across disconnects
  • VS Code restarts
  • Long-running work

Example prompts

  • “/nemo-rl-session-memory”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Check for existing session directories
  2. If the user is resuming work, read the latest relevant session_state.md, timeline.md, and handoff.md.
  3. If no relevant session exists, create a new timestamped directory.
  4. Write an initial session_state.md with the user's overall goal, current subtask, loaded skills, repo path, branch, and known constraints.

What it can do on your machine

Read from SKILL.md and the folder at commit 0e0d506. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Nemo Rl Session Memory loads about 1.4k tokens when it runs. Until then it costs about 100 tokens; SKILL.md has 465 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from NVIDIA/skills at commit 0e0d506, republished under its Apache-2.0 licence (© NVIDIA). 465 words, ~1,363 tokens.

Download SKILL.mdSave it as .claude/skills/nemo-rl-session-memory/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
nemo-rl-session-memory
description
Manage durable working-session memory for coding agents. Use when a user asks to preserve or recover agent context across disconnects, VS Code restarts, long-running work, handoffs, or any session where important state should be written periodically under the repo's session directory. Do NOT use for: simple questions, short tasks, one-off commands, linting, or code review.
license
Apache-2.0
when_to_use
Preserving or recovering coding-agent context; creating checkpoints for long-running work, handoffs, disconnects, VS Code restarts, branch switches, or…

Session Memory

Keep a durable, human-readable record of the current working session so another agent can resume after a disconnect with minimal context loss.

When To Use

Use this skill when:

  • The user asks to preserve, recover, checkpoint, or manage agent memory.
  • Work is long-running, experimental, or likely to span disconnects.
  • You are about to make nontrivial edits, run long jobs, switch branches, or pause for user input.
  • You resume in a repo that already has ./session/ directories.

Session Directory

Create one directory per working session:

bash
mkdir -p session
date +%Y%m%d_%H%M%S
mkdir -p session/<session_date_time>

Use local time from the machine. Reuse the same session directory for all checkpoints in the same conversation unless the user explicitly starts a new session.

Expected files:

  • session_state.md - overall goal, current subtask, loaded skills, status, plan, assumptions, blockers, and next actions.
  • timeline.md - append-only log of major actions, commands, results, and decisions.
  • files.md - files inspected, files changed, and why they matter.
  • handoff.md - concise resume instructions for the next agent.

Add other files only when useful, such as experiments.tsv, review_notes.md, or copied command logs.

Start Or Resume

At the start of a session:

  1. Check for existing session directories:
bash
ls -dt session/* 2>/dev/null | head
  1. If the user is resuming work, read the latest relevant session_state.md, timeline.md, and handoff.md.
  2. If no relevant session exists, create a new timestamped directory.
  3. Write an initial session_state.md with the user's overall goal, current subtask, loaded skills, repo path, branch, and known constraints.

Do not treat session notes as the only source of truth. Verify important claims against git state, files, and command output before acting.

Show full SKILL.md (212 more words)Show less

Checkpoint Rhythm

Write a checkpoint:

  • After gathering enough context to form a plan.
  • Before and after meaningful code edits.
  • Before long-running commands, experiments, branch switches, or anything hard to reconstruct from chat.
  • When the user changes direction.
  • Before final response if the session has meaningful state worth resuming.
  • At least every 30 minutes during active long-running work.

Prefer updating the same files rather than creating many small checkpoint files. Keep the record compact and scannable.

File Templates

session_state.md
markdown
# Session State

- Session: <session_date_time>
- Repo: <absolute repo path>
- Branch: <branch name>
- Started: <local timestamp>
- Updated: <local timestamp>

## Goal
<Stable overall user goal in one or two sentences. Preserve this across follow-up steering unless the user explicitly changes it.>

## Current Subtask
<Immediate task or steering request currently being handled.>

## Loaded Skills
- `<skill-name>` - <why it was loaded and any important instructions to preserve.>

## Current Status
<What is true now. Include completed work and verification status.>

## Plan
- [ ] <Next concrete step>
- [ ] <Next concrete step>

## Assumptions
- <Assumption and how to verify it if needed.>

## Blockers
- <Blocker or "None known".>
timeline.md
markdown
# Timeline

## <local timestamp>
- User asked: <brief request>
- Context gathered: <files/commands and key result>
- Decision: <important choice and rationale>
- Result: <edits/tests/outcome>
files.md
markdown
# Files

## Inspected
- `<path>` - <why it mattered>

## Changed
- `<path>` - <what changed and why>

## Generated
- `<path>` - <purpose>
handoff.md
markdown
# Handoff

## Resume From Here
<One paragraph summary of the current state.>

## Next Actions
- <Most important next action>
- <Verification or cleanup still needed>

## Watch Outs
- <Risks, user preferences, or repo constraints the next agent must preserve.>

Recovery Workflow

When resuming after a disconnect:

  1. Find the likely latest session directory.
  2. Read handoff.md first, then session_state.md, then recent timeline.md.
  3. Run lightweight verification such as git status --short, git branch --show-current, and targeted file reads.
  4. Continue from the latest verified next action.
  5. Append a timeline entry noting the recovery and any mismatches found.

Quality Rules

  • Keep notes factual and terse. Future agents need state, not a transcript.
  • Record command outcomes that matter, especially failed tests or skipped verification.
  • Mention uncommitted changes and whether they were made by the current agent or pre-existing.
  • Do not store secrets, tokens, private credentials, or large logs in session files.
  • If a session file becomes large, summarize old details and keep the latest next actions near the top of handoff.md.

© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files in skills/nemo-rl-session-memory of NVIDIA/skills.

  • SKILL.md
  • BENCHMARK.md
  • evals/evals.json
  • skill-card.md
  • skill.oms.sig

Open the folder on GitHubat commit 0e0d506

Compare with similar skills

Nemo Rl Session Memory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Nemo Rl Session Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Nemo Rl Session Memory this skillNVIDIA/skills3.5k—~1.4kAutomated safety check: PassApache-2.0
Using LWC Memory and Graphssickn33/agentic-awesome-skills47k1 repos~2kAutomated safety check: PassApache-2.0
Harness Engineering10xChengTu/harness-engineering1021 repos~1kAutomated safety check: PassNone
Beads Task Memorygastownhall/beads28k—~1.2kAutomated safety check: PassMIT
CodemapJordanCoin/codemap704—~1.8kAutomated safety check: PassMIT
Agnixagent-sh/agnix444—~874Automated safety check: PassApache-2.0

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Questions about Nemo Rl Session Memory

What does Nemo Rl Session Memory do?

Manage durable working-session memory for coding agents. An agent skill from NVIDIA/skills. Nemo Rl Session Memory is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Manage durable working-session memory for coding agents.

When should I use Nemo Rl Session Memory?

Nemo Rl Session Memory fits situations like: A user asks to preserve; recover agent context across disconnects; VS Code restarts; long-running work.

How do I install Nemo Rl Session Memory in Claude Code?

Run `npx skills add NVIDIA/skills --skill nemo-rl-session-memory -a claude-code`. Or copy the skill folder (skills/nemo-rl-session-memory in NVIDIA/skills) into .claude/skills/nemo-rl-session-memory in your project. Claude Code loads it when a task matches its description.

How do I install Nemo Rl Session Memory in Codex?

Run `npx skills add NVIDIA/skills --skill nemo-rl-session-memory -a codex`. Or copy the skill folder (skills/nemo-rl-session-memory in NVIDIA/skills) into .agents/skills/nemo-rl-session-memory in your project. Codex loads it when a task matches its description.

Can I use Nemo Rl Session Memory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill nemo-rl-session-memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nemo-rl-session-memory, .gemini/skills/nemo-rl-session-memory, .github/skills/nemo-rl-session-memory and .opencode/skills/nemo-rl-session-memory in your project.

What does Nemo Rl Session Memory need to run?

Going by SKILL.md and its folder, Nemo Rl Session Memory needs the command-line tools its instructions call (git).

Does Nemo Rl Session Memory access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Nemo Rl Session Memory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Nemo Rl Session Memory use?

Nemo Rl Session Memory is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Nemo Rl Session Memory use?

About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Nemo Rl Session Memory?

Skills that share tags, products or a category with Nemo Rl Session Memory: Using LWC Memory and Graphs (sickn33/agentic-awesome-skills, 47k stars), Harness Engineering (10xChengTu/harness-engineering, 102 stars), Beads Task Memory (gastownhall/beads, 28k stars) and Codemap (JordanCoin/codemap, 704 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Nemo Rl Session Memory?

NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,534 GitHub stars. The repository holds 380 skills in this directory. The repository was last updated on October 7, 2026.

Source: NVIDIA/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.