acme
Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
Skill by VectorSpaceLab
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/vectorspacelab-acme
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: data, ml
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/acme
What's inside
- Skill name
acme- Description
- Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
- License
- Apache-2.0
- Metadata
- disco-role: operating
- Instructions
- 46 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (27)
- SKILL.md
- package-overview.md · references/
- repo-provenance.md · references/
- repo-routing-metadata.json · references/
- troubleshooting.md · references/
- check_acme_skill_runtime.py · scripts/
- SKILL.md · sub-skills/core-workflows/
- core-api.md · sub-skills/core-workflows/references/
- troubleshooting.md · sub-skills/core-workflows/references/
- workflows.md · sub-skills/core-workflows/references/
- check_core_imports.py · sub-skills/core-workflows/scripts/
- SKILL.md · sub-skills/jax-agents/
- agent-catalog.md · sub-skills/jax-agents/references/
- api-reference.md · sub-skills/jax-agents/references/
- experiment-workflows.md · sub-skills/jax-agents/references/
- troubleshooting.md · sub-skills/jax-agents/references/
- select_jax_agent.py · sub-skills/jax-agents/scripts/
- SKILL.md · sub-skills/replay-and-data/
- replay-api.md · sub-skills/replay-and-data/references/
- troubleshooting.md · sub-skills/replay-and-data/references/
- workflows.md · sub-skills/replay-and-data/references/
- describe_replay_structure.py · sub-skills/replay-and-data/scripts/
- SKILL.md · sub-skills/tf-agents/
- agent-catalog.md · sub-skills/tf-agents/references/
- network-and-saver-workflows.md · sub-skills/tf-agents/references/
- troubleshooting.md · sub-skills/tf-agents/references/
- select_tf_agent.py · sub-skills/tf-agents/scripts/
SKILL.md (first lines)
# Acme Repo Skill Use this repo skill when a user asks about DeepMind Acme (`dm-acme`), Acme-style reinforcement-learning agents, `dm_env` loops, Reverb adders, Acme JAX experiments, or Acme TensorFlow/Sonnet agents. ## Start Here - Read [references/repo-provenance.md](references/repo-provenance.md) before deciding whether this skill matches a current checkout or should be refreshed. - Read [references/package-overview.md](references/package-overview.md) for install extras, public dependency groups, repository capability map, and optional-backend expectations. - Read [references/troubleshooting.md](references/troubleshooting.md) for cross-cutting install/import, optional dependency, backend, and example-runtime failures. - Run `python scripts/check_acme_skill_runtime.py --help` for a bundled, dependency-light helper that explains package import checks and available sub-skill helper scripts. ## Route By Task - **Core loops/specs/wrappers:** use [sub-skills/core-workflows/SKILL.md](sub-skills/core-workflows/SKILL.md) for `dm_env` specs, `Actor`/`Learner`, `EnvironmentLoop`, wrappers, loggers, counters, observers, and simple custom loop debugging. - **Replay and data:** use [sub-skills/replay-and-data/SKILL.md](sub-skills/replay-and-data/SKILL.md) for `Adder` contracts, Reverb adders, replay tables, dataset iterators, TFDS/offline data, and transition/sequence/episode shape decisions. - **JAX agents:** use [sub-skills/jax-agents/SKILL.md](sub-skills/jax-agents/SKILL.md) for Acme JAX algorithms, `acme.jax.experiments`, Haiku/Optax/RLax networks, online/offline/distributed JAX workflows, and JAX multiagent examples. - **TensorFlow agents:** use [sub-skills/tf-agents/SKILL.md](sub-skills/tf-agents/SKILL.md) for Acme TensorFlow/Sonnet algorithms, TF losses, TF savers/snapshotters, Launchpad TF examples, and TF learner debugging. ## Install Baseline - Distribution name: `dm-acme`; import package: `acme`; snapshot version: `0.4.1`. - Minimal package metadata lists core requirements: `absl-py`, `dm-env`, `dm-tree`, `numpy`, `pillow`, and `typing-extensions`. - Real agent execution usually needs optional extras: `dm-acme[jax]` for JAX agents, `dm-acme[tf]` for TensorFlow/Reverb/Launchpad agents, and `dm-acme[envs]` for example environments. - Treat optional extras as backend/runtime choices, not as always-required imports. Many examples require Gym, bsuite, Control Suite, Atari ROMs, OpenSpiel, Reverb servers, Launchpad launch modes, or long training budgets. ## Minimal Import Check ```bash python - <<'PY' import acme from acme import specs print(acme.__version__) print(specs.Array((2,), float)) PY ``` If this fails with `ModuleNotFoundError` for `jax`, `tensorflow`, `reverb`, `launchpad`, `gym`, `bsuite`, or environment packages, read [references/troubleshooting.md](references/troubleshooting.md) before broadening installs. ## Skill Boundaries - This skill is for using, adapting, troubleshooting, and explaining Acme as an RL framework; it is not a benchmark reproduction plan and does not verify long training results. - Do not route generic RL theory questions here unless the task names Acme APIs, Acme examples, or Acme-style builders/adders/loops. - Do not tell future agents to open or run original repository files. This skill distills the repo evidence into bundled references and scripts. - For source drift, compare current commit, dirty state, package metadata, and evidence paths with [references/repo-provenance.md](references/repo-provenance.md), then run `refresh-repo-skill` if they differ.
From VectorSpaceLab/AREX-Skill, Apache-2.0.
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Signals
- Stars
- 341
- Forks
- 26
- Open issues
- 0
- Last commit (this folder)
- Aug 26, 2026 (2 months ago)
- Last release
- Sep 2, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/VectorSpaceLab/AREX-Skill
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
acme skill. Agent Mart. https://agentmart.dev/skills/vectorspacelab-acme (last updated 2026-10-24)