> ## Documentation Index
> Fetch the complete documentation index at: https://docs.decimal.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Trust & Exit

> What you're actually depending on when you adopt DecimalAI — open formats, no code in your LLM critical path, everything exportable — and what leaving looks like.

Adopting an agent platform is a trust decision, so here is the dependency surface stated plainly: which formats are open, where our code sits relative to your agent, what you can take with you, and what breaks (nothing) if you leave. The short version: **the artifacts are open, the clients are open source, and the hosted platform earns its keep with evidence — not lock-in.**

## The formats are open

Everything DecimalAI produces on your side of the fence is a documented, openly specified artifact you can read, generate, and verify without us:

| Artifact          | Format                                                                                                              | Spec                                                                                            |
| ----------------- | ------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------- |
| A skill           | `SKILL.md` — plain markdown + YAML frontmatter, per the open [agentskills.io](https://agentskills.io) specification | Readable by Claude Code, Cursor, Copilot, Cline, and anything else that scans skill directories |
| A skill benchmark | `eval.yaml` — declarative A/B test cases                                                                            | [skillevaluation](/guides/skillevaluation), an open spec **and** reference runner on PyPI       |
| An agent version  | Manifest + diff + compatibility decision                                                                            | [agentversion](/concepts/versioning), the open spec the platform is built on, also on PyPI      |

Two consequences worth spelling out:

* **A skill you install from the registry is yours as a file.** It isn't a pointer into our database — it's markdown on your disk that keeps working if DecimalAI disappears tomorrow.
* **Every number we publish is reproducible.** A verified lift figure comes from an `eval.yaml` run under the skillevaluation spec; pull the skill and its suite (`decimalai skills pull <slug>`) and re-run the benchmark on your own machine with the open runner. You don't have to trust our leaderboard — you can check it.

<Note>
  agentversion and skillevaluation are open **specs** — published formats with reference implementations anyone can build against. We deliberately don't call them standards; a standard is earned by adoption, not declared by a vendor.
</Note>

## No DecimalAI code in your LLM critical path

The SDK is an observer, not a proxy. Your agent calls your LLM provider directly, with your keys, exactly as it did before:

* **Tracing is fire-and-forget.** Traces are queued to a background sender; your agent never waits on our API to answer your users.
* **We never see your LLM credentials.** Regression checks are pure trace-store queries — we don't run your agent. The one place a key is used ([Playground](/guides/playground) runs) is bring-your-own-key, from your browser session.
* **Skill delivery degrades gracefully.** Skills exported to disk load without any network call — that's your runtime reading a local file. If you use hosted routing and the platform is unreachable, the SDK falls back to local-only mode: your agent runs, skills still load from disk, and you lose telemetry for the gap — not uptime.

The blunt test: **turn DecimalAI off and your agent still works.** You lose the measurement layer — regression checks, effectiveness data, routing telemetry — which is the product. You don't lose your agent.

## Everything is exportable

| What                                 | How                                                                                                                       | Auth    |
| ------------------------------------ | ------------------------------------------------------------------------------------------------------------------------- | ------- |
| Any public skill (+ its eval suite)  | `decimalai skills pull <slug>` — or the [raw URLs](/guides/use-skills-without-the-sdk#raw-urls-scripts-ci-and-llm-agents) | None    |
| All of your org's skills             | `GET /api/v1/skills/export` — bulk export, ready for disk                                                                 | API key |
| Your skills, onto disk, continuously | [Bidirectional sync](/guides/skills#bidirectional-sync) keeps `SKILL.md` files in your repo, not just in our DB           | API key |
| Training datasets                    | `decimalai datasets pull <id>` → JSONL on your disk                                                                       | API key |
| Your traces                          | `GET /api/v1/traces` (list + full detail), replay batches via `GET /api/v1/replay/export`                                 | API key |
| Benchmark methodology                | The [skillevaluation](/guides/skillevaluation) runner is on PyPI — re-run any verified number offline                     | None    |

Deleting is a first-class exit too: workspace deletion purges traces, manifests, datasets, and skills — see "How do I delete my data?" in the [FAQ](/faq).

## The client tooling is open source

Every piece of DecimalAI code that runs on *your* machines is permissively licensed:

| Tool                     | What it is                                                      | License    |
| ------------------------ | --------------------------------------------------------------- | ---------- |
| `decimalai` (PyPI)       | Python SDK + CLI                                                | MIT        |
| `agentversion` (PyPI)    | Manifest / diff / compatibility spec + reference implementation | Apache-2.0 |
| `skillevaluation` (PyPI) | Skill A/B benchmark spec + reference runner                     | Apache-2.0 |
| `regression-check`       | GitHub Action for PR impact reports                             | MIT        |
| `decimalai` (npm)        | npx skill installer                                             | MIT        |
| `decimalai-mcp` (PyPI)   | MCP server over the public registry                             | MIT        |
| Claude Code plugin       | `/decimalai:*` commands                                         | MIT        |

Permissive licensing is the point: if we vanish, the tooling you depend on is forkable, and the file formats it reads and writes are specified above.

## What is *not* open — and why

Honesty cuts both ways. The hosted platform — the trace store, the registry, the dashboard, and the verified-benchmark runner — is a cloud service, not an open-source deployment, and self-hosting isn't offered today. The centralization is deliberate in exactly one place: **verified runs execute on our infrastructure**, which is what makes a "verified" lift number mean something — a self-reported benchmark can't poison the leaderboard. You can reproduce any number locally with the open runner; you can't *mint* a verified badge locally. That's the trade, stated plainly.

Everything on your side of that line — your files, your data, your tooling — exits cleanly.

## Related

* [Use skills without the SDK](/guides/use-skills-without-the-sdk) — every consume-only route, no account required
* [Security](/security) — data handling, retention, encryption
* [Why DecimalAI?](/guides/why-decimalai) — feature comparison, including where competitors are more open (Langfuse self-hosts; we don't yet)
* [skillevaluation](/guides/skillevaluation) and [Versioning & Compatibility](/concepts/versioning) — the two open specs in detail
