active|loom
ActiveLoom / reusable workflows for coding agents

Give your agents discipline.
Prove every commit.

Coding agents write code fast, but without guardrails they regress, hallucinate passing reviews, and burn tokens in loops. ActiveLoom supplies battle-tested skills, PR-first adversarial review protocols, verifiable commit ledgers, and bounded issue autonomy for Claude Code, Codex, and Gemini — synced from one upstream to your entire repository fleet.

$ npx activeloom init --harness codex,claude,gemini
Claude Code OpenAI Codex Google Antigravity / Gemini Node 18+ & Python 3.9+ Apache 2.0
3
Native Agent Harnesses
10+
Production Skills
100%
Verifiable Commit Evidence
Apache 2.0
Permissive Open Source
Live Protocol Simulator

The multi-agent workflow in action.

Click any agent, workspace, or tab to inspect live protocol evidence ↗

activeloom-session — 3 workspaces · 4 agents
Codex on ~/wt/activescribe-streaming-r2 > feat/audio-stream
activeloom critique deep --pr 242
[protocol] Draft PR #242 verified. Review tier resolved: DEEP (Trigger 2: Audio mutation & encryption boundary)
[protocol] Preflight diff validation: 4 files changed, +142 lines, -18 lines.
[protocol] Executing adversarial pass across 5 deep review lanes...
DEFECT DETECTED: Unencrypted database update on encrypted column
File: apps/backend/src/transcription/stream.service.ts#L142
Violation: Column `bx_raw_payload` updated directly without `e_id` encapsulation. Violates HIPAA/PHIPA encryption invariant.
Posted verified defect inline to PR #242 comment thread (commit: 4d2e1b).
Automated fix diff prepared using safeEncryptedUpdate() from shared package.
Awaiting second-opinion verification from Gemini... (42s elapsed)
ctx: 4% (38k / 1M)
Capabilities

Engineered for teams that treat agent code like production code.

ActiveLoom replaces fragile ad-hoc system prompts with structured engineering discipline, rigorous review ledgers, and deterministic fleet sync.

01 SKILLS & WORKFLOWS

Not chat prompts. Operational skills.

ActiveLoom skills encode strict operational procedures with validation checklists and deterministic outputs. From pre-code requirements grilling (grill) and deep troubleshooting (diagnosing-bugs) to task packets.

/diagnosing-bugs READY
Step 1: Reproduce defect in isolation
Step 2: Root cause analysis (no guessing)
Step 3: Smallest meaningful fix + regression test
02 MULTI-ENGINE PARITY

Claude, Codex, and Gemini in sync.

Don't maintain three divergent prompt trees. ActiveLoom authors skills once in prompts/ and renders them natively into .claude/, .codex/, and .agents/ (Gemini / Antigravity).

One upstream definition 3 native outputs
Claude Code
OpenAI Codex
Gemini / Agy
03 REVIEW PROTOCOL

Adversarial review. Proof before edit.

No rubber-stamping. Reviewers must inspect draft PR diffs and post verified findings inline to GitHub before touching any code. Automated tier gating resolves Lean (fast critical check) or Deep (exhaustive matrix).

Review Tier Gate: Deep Tier
Trigger: Encryption, Auth & Telemetry boundaries
✓ Findings posted inline before code fix
04 CRYPTOGRAPHIC LEDGERS

Verifiable proof for every commit.

A machine-readable review-ledger.json binds review evidence, passing invariants, and multi-engine signatures directly to a specific Git commit SHA. If someone amends the commit, the ledger invalidates.

review-ledger.json SHA MATCHED
Commit: 4d2e1b89ef01a23c7b89...
✓ Signed by Codex + Gemini second-opinion
05 BOUNDED AUTONOMY

Autonomous queues with guardrails.

Let agents work your GitHub backlog safely with agent-loop. Strict issue allowlists, one isolated Git worktree per issue (~/wt/*), test-driven iteration, and automatic bail-outs when blocked.

CLI Tape Demo: LIVE
$
06 FLEET DISTRIBUTION

Sync 50 repos without losing local rules.

ActiveLoom's sync engine propagates skills and review updates via PRs (sync-v2) while strictly protecting consumer-owned security rules in .review/addendum.local.md.

Upstream: activeloom@sync-v2 PR #6482
Syncs: Core skills, review workflows
★ Local addenda & project rules strictly preserved
Hard Boundaries

What ActiveLoom deliberately does NOT do.

Software engineering tools earn trust through explicit non-goals. We don't lock you into a cloud, hide the prompts, or replace human review.

What ActiveLoom delivers
  • Standardized engineering skills: Planning, debugging, and review workflows that any team agent can invoke.
  • PR-first adversarial review: Verified findings posted inline to GitHub before code modifications occur.
  • Cryptographic review ledgers: Machine-readable proof of review convergence tied directly to git commit SHAs.
  • Upstream fleet sync: Keep 50 repositories updated via automated PRs without clobbering repo-local rules.
What we deliberately avoid
  • No proprietary agent runtime: Bring your own Claude Code, OpenAI Codex, or Gemini CLI. No vendor lock-in.
  • No monthly SaaS seat tax: No hosted workspace fees, no credit tokens. 100% open source and self-contained.
  • No silent auto-merges: Agents never push directly to main or merge unvetted PRs. Every change requires human review.
  • No clobbering of local rules: Upstream prompt improvements never overwrite your repository's custom compliance invariants.
Adoption Model

From personal trial to fleet sync.

Adopt gradually. Start by running a single skill in your personal shell, then scale up to scheduled multi-repo propagation.

Tier 0

Personal Evaluation

Try a single skill in your home directory without touching any shared repository files or configurations.

$ activeloom add critique
Tier 1

Repository Setup

Scaffold harness directories (.codex/, .claude/) and shared project instructions for your team.

$ activeloom init
Recommended
Tier 2

Scheduled Sync

Automated GitHub Actions workflow proposing upstream skill improvements via pull requests using built-in GITHUB_TOKEN.

$ activeloom init --sync
Tier 3

App-Backed Fleet

Enterprise multi-repo orchestration. Scheduled updates with cryptographic GitHub App signatures and least-privilege tokens.

$ activeloom init --sync --app
Ready to evaluate?

Give your agents real discipline today.

One command to initialize your repository. Nothing about your developer workflow changes, except now your AI agents work with verifiable proof.

$ npx activeloom init --harness codex,claude,gemini
Requires Node 18.17+ and Python 3.9+ · Zero runtime telemetry sent to third parties