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

# AutoSci Profile

> Use AutoSci as a complete example of profiles-as-configuration.

AutoSci is a built-in profile template for research projects. It is useful both
as a ready-to-use research workspace and as a concrete example of how profiles
compose entities, relations, lifecycles, artifacts, workflows, connector
bindings, and trust rules without profile-specific code.

AutoSci is the largest built-in example of
[Configurable Lifecycle Profiles](/concepts/configurable-lifecycle-profiles):
the domain behavior comes from profile data, while the core engine stays
generic.

## Install AutoSci

```bash theme={null}
llmwiki template inspect autosci
llmwiki template init autosci
llmwiki profile validate
```

`template init autosci` writes `.llmwiki/profile.json` after confirming the
typed corpus is empty. The installed profile has `profileId: autosci`.

## What AutoSci declares

| Capability | AutoSci |
| - | - |
| Entities | 12 |
| Relations | 12 |
| Workflows | 5 |
| Workflow actions | 5 |
| Artifact types | 7 |
| Connector bindings | `crossref` |
| Content tiers | yes |
| Relation preconditions | yes |
| Artifact preconditions | yes |

## Entity vocabulary

AutoSci's entities model a research workflow:

| Entity type | Directory | Role |
| - | - | - |
| `papers` | `wiki/papers` | Imported and distilled literature |
| `sources` | `wiki/sources` | Repositories, videos, web pages, and paper sources |
| `ideas` | `wiki/ideas` | Proposed, explored, validated, or rejected hypotheses |
| `experiments` | `wiki/experiments` | Designs, running experiments, and completed results |
| `manuscripts` | `wiki/manuscripts` | Drafting, citation-checking, and submission |
| `topics` | `wiki/topics` | Research areas and gaps |
| `research-concepts` | `wiki/research-concepts` | Domain concepts extracted from literature |
| `methods` | `wiki/methods` | Proposed, validated, or deprecated methods |
| `foundations` | `wiki/foundations` | Datasets, tools, theories, and benchmarks |
| `people` | `wiki/people` | Researchers and collaborators |
| `reviews` | `wiki/reviews` | Peer review and internal review records |
| `research-outputs` | `wiki/research-outputs` | Released models, datasets, reports, and code |

## Relations

AutoSci relations are typed and endpoint-checked:

```json theme={null}
{
  "tests": {
    "from": ["experiments"],
    "to": ["ideas"],
    "direction": "directed"
  },
  "cites": {
    "from": ["papers", "manuscripts"],
    "to": ["sources", "papers"],
    "direction": "directed"
  },
  "builds-on": {
    "from": ["ideas"],
    "to": ["papers", "ideas"],
    "direction": "directed"
  }
}
```

The full profile also includes `challenges`, `introduces-concept`,
`uses-concept`, `proposes-method`, `extends-method`, `supports`,
`contradicts`, `derived-from`, and `addresses-gap`.

## Lifecycle gates

AutoSci uses lifecycle fields to keep state transitions explicit. For example,
an experiment starts as `designed`, moves to `running`, and can enter `complete`
only when it has a `resultSummary`, a live `tests` relation to an idea, and a
healthy `experiment-result` artifact ref.

```yaml theme={null}
---
title: Sparse attention ablation
hypothesis: Sparse attention improves latency.
stage: complete
resultSummary: Sparse attention improved p95 latency.
result: experiment-result/sparse-attention@sha256:4b7...
---
```

That frontmatter is accepted only if the referenced artifact exists and matches
the pinned hash, and the relation graph contains the required `tests` edge.

## Artifacts

AutoSci declares seven artifact types:

| Artifact type | File name | Content kind |
| - | - | - |
| `experiment-result` | `result.json` | JSON |
| `paper-source-metadata` | `source-metadata.json` | JSON |
| `experiment-plan` | `plan.json` | JSON |
| `run-log` | `run.txt` | text |
| `manuscript-draft` | `draft.md` | text |
| `review-packet` | `packet.json` | JSON |
| `rebuttal-response` | `rebuttal.md` | text |

Artifacts are written with `llmwiki artifact write` or as workflow artifact
outputs. Pages reference them with `artifactRef` fields.

## Workflows

AutoSci ships five workflows:

| Workflow | Purpose |
| - | - |
| `literature-review` | Gather papers, extract concepts, and synthesize topics |
| `research` | Move from paper import through idea and experiment completion |
| `manuscript-writing` | Draft, cite, check, and submit a manuscript |
| `experiment-design` | Propose methods and design experiments |
| `review-response` | Intake reviews and draft responses |

Each workflow is declared in the profile. The core workflow engine has no
AutoSci-specific branches.

## Crossref binding

AutoSci binds the first-party `crossref` connector to `papers`:

```json theme={null}
{
  "crossref": {
    "entityType": "papers",
    "fields": {
      "title": "title",
      "doi": "doi",
      "year": "year",
      "authors": "authors",
      "stage": "stage"
    },
    "contentField": "abstract"
  }
}
```

Running Crossref stages a typed `papers` review candidate. Approval requires the
operator-supplied draft content hash printed by `review show`.

## Why AutoSci is a configuration example

AutoSci proves the profile model by expressing a rich research workflow as data:

* entity directories and field contracts;
* typed relations;
* finite-state lifecycles;
* relation and artifact preconditions;
* declared workflow stages and actions;
* artifact contracts;
* connector bindings;
* content tiers.

The default profile, AutoSci, and Newsroom all use the same core engine. Profile
behavior comes from `.llmwiki/profile.json`, not from domain-specific branches.


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