reelier
Reelier is a CI/snapshot-testing tool for AI agent tool-call workflows — it records, replays, diffs, and publishes verifiable receipts of agent runs at zero LLM cost.
reelier_scan— Discover replayable workflows from past agent session histories (e.g.,~/.claude/projects), identifying transcripts with MCP/HTTP tool-call sequences worth compiling into a skill.reelier_from_session— Compile a session transcript into a portableSKILL.mdfile (replayable skill), flagging open questions like relative time windows that need variable binding.reelier_replay— Deterministically replay a skill at Level 0 (zero LLM calls), returning per-step outcomes, timing, and drift reasons. Read-only by default, with options to permit idempotent-write or destructive steps.reelier_diff— Compare two runs of the same skill, reportingSAMEorDRIFTEDper step with the failing assertion as the reason. Useful for gating dependency bumps (e.g., Dependabot/Renovate) or scheduled regression checks in CI.reelier_push— Push local run records (and optionally the skill file) to the Reelier Cloud receipt ledger, generating a shareable permalink and embeddable verified-replay badge.
Gates Dependabot bump PRs by replaying recorded skill workflows against the updated dependency, detecting drifts in tool-call behavior without LLM calls.
Gates Renovate bump PRs by replaying recorded skill workflows against the updated dependency, detecting drifts in tool-call behavior without LLM calls.
Reelier
Let your agents write. Keep the receipts.
Your agents worked all night. Here's exactly what changed.
Reelier records the run that worked, freezes it as a replayable skill, and replays it deterministically — every run comes back as a receipt: proof of what the agent did and what changed because of it. Agents make claims. Reelier writes receipts.
▶ watch with sound (27s)
Receipts on your agent PRs — install and done
Agent-authored PRs (Dependabot, Claude, Codex, Cursor, …) get a receipt comment in seconds: author, files changed, declared scope vs. what actually changed, sensitive paths flagged. No workflow file, no CLI, no config.
→ Install the Reelier receipts GitHub App — free on public repos, forever.
Reelier receipt — agent PR Author:
dependabot[bot]· Files changed: 2 (+119 −41) Declared scope: none (add.reelier/scope.ymlto enable unexpected-write detection) Sensitive paths touched: ⚠ 1 —package-lock.jsonProves scope and change, not correctness
A real receipt from Reelier's own repos — see one live. Declare scope per agent in .reelier/scope.yml (or a reelier-scope block in the PR body) and the receipt reports unexpected writes. The receipt proves scope and change, never correctness or safety.
Related MCP server: @humanaccepted/mcp
Why
AI agents are non-deterministic — the same prompt, a different result every run — and they'll claim they did the work whether they did or not. Reelier records the run that worked, replays it deterministically, and writes a signed receipt that proves it. Point it at your existing CI in one workflow — it adds a verifiable receipt, it doesn't replace your stack.
Measured on a real head-to-head benchmark, same task, same data (full method):
1,000 / 1,000 replays byte-identical
Every replay ships a signed receipt — proof of what ran and what changed, never a claim
0 LLM calls at replay — deterministic re-execution, not re-reasoning
Deterministic replay is also ~50× cheaper and ~59× faster than re-running the agent, on the same benchmark.
Install
npm i -g reelier && reelier init# No Node install needed — same commands via Docker:
docker run --rm ghcr.io/seldonframe/reelier --helpreelier init scans work you've already done (Claude Code, Codex, OpenClaw) into a real skill, or falls back to a zero-setup demo with a real receipt in under 60 seconds.
How to use it
reelier init # 60s: record → compile → replay → your receipt
reelier run <name>.skill.md # replay deterministically — 0 tokens (read-only by default)
reelier diff <name> # SAME or DRIFTED, per step — exit 1 on drift
reelier push <name>.skill.md # sync receipts to your ledger (opt-in)
reelier ci # write a workflow: drift-CI + PR receipts, one commandRecord.
reelier mcp --wrap "<mcp server>"proxies your tools live, or pull a session viareelier scan/from-session, or run the guidedreelier init.Compile.
reelier compileturns a trace into aSKILL.md— 0 LLM calls, minimal assertions, honest gaps printed as Open questions.Replay.
reelier runreplays it at Level 0 — no LLM, byte-identical, read-only by default (writes need--allow-writes).Diff.
reelier diffreports SAME or DRIFTED per step, with the failing assertion as the why — exit 1 on drift.Log in.
reelier loginconnects this machine to Reelier Cloud with a device code in your browser — or setREELIER_CLOUD_URL/REELIER_CLOUD_KEYfor CI and self-hosting.Push. Every run is a receipt;
reelier pushoptionally syncs it to a ledger for a permalink and an embeddable verified-replay badge.
Already have an Agent Skill? Convert it — your skill, minus the model:
reelier compile trace.jsonl --from-skill ./my-skill/SKILL.mdThree tests, one skill
Test | Command | Answers |
Determinism |
| Does this still do what it did? |
Recovery |
| If this broke, would the skill notice and heal? |
Drift |
| Has the world moved out from under this skill? |
Taxonomy due to Mads Hansen's review of the launch post. Full semantics for each test, including recovery injection and manifest guardrails: docs/REFERENCE.md.
Gate Dependabot / Renovate bump PRs
Dependabot and Renovate open the PR and run your test suite — but neither knows what your agent actually does at runtime, so a dependency bump that silently changes a tool call's shape (a renamed field, a new default, a different error) sails through with green unit tests. This is the check they don't run.
Copy .github/workflows/reelier-bump-check.yml into your repo, point skill: at your own recorded .skill.md file(s), and it will: gate to PRs from dependabot[bot]/renovate[bot] (or a dependencies label), install the bumped dependency, replay your recorded skill live against it at --max-level 0 (0 tokens), and fail the check on the exact step that drifted.
This tests dependency and MCP-tool-call behavior — it does not test model upgrades; --max-level 0 never calls an LLM. Full listing copy and setup: docs/marketplace-listing.md.
Prove it
A pushed receipt carries a ladder of independently-verifiable claims — not one blanket "verified." Depending on what you turn on, it can be signed, timestamped, CI-attested, and carry cross-checkable provider request-ids. reelier verify recomputes every claim offline, and a claim you haven't enabled just renders as an honest gap, never a shamed one.
See a real one: reelier.com/r/HWBdmGob9KeHRqXi-OEaRD0z.
Full 8-rung ladder, what each rung does and doesn't prove: docs/REFERENCE.md.
If your skills are employees
Employee lifecycle | Reelier equivalent |
Skillify a session |
|
Performance review |
|
Fleet maintenance | scheduled replays + drift alerts |
The record | signed receipts |
"Verified" describes the record, never the agent — a receipt proves what ran and what changed, not that the agent was good at its job.
An employment contract doesn't make an employee good — it makes what they did visible and bounded. Same here: receipts prove scope and change, never correctness.
Who it's for
Solo dev / OSS maintainer — a real regression test again; drift can't pass silently.
Team shipping agent changes — "it ran clean" becomes a checkable PR artifact, not a claim.
Agency running agents for clients — signed, timestamped proof-of-delivery a client can verify.
Marketplace buyer or seller — corroborated receipts are reviews that can't be astroturfed.
Audit-facing ops — a signed, CI-attested trail of every write, idempotency key included.
MIT, free forever (versions ≤0.16.0 remain AGPL-3.0). Your data — skills, traces, runs — is specified in SPEC.md, so leaving is copying a folder.
Contributing: issues and PRs welcome — SPEC.md is the source of truth for formats; fix the code, not the spec. npm test before a PR.
If Reelier saved you a re-run, star it ⭐ — it's how other builders find it.
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