@peat_shade/auto-ledger-25
AI-assisted analysis of rubric-scored evaluations. Returns rubric-scored JSON suitable for downstream judging.
## Quick start
Add `@peat_shade/auto-ledger-25` to your repo's `extensions` list, then reference its model in your `swamp.yaml`:
```yaml
extensions:
- @peat_shade/auto-ledger-25
workflows:
- name: auto-ledger-25-run
jobs:
- name: main
steps:
- name: get
model: peat_shade/auto-ledger-25
method: get
```
Run with `swamp workflow run auto-ledger-25-run`. The first invocation prints what it would change; pass `--apply` to commit.
## What's inside
- **Typed models** — Zod-validated arguments, structured outputs, and a manifest the agent can reason about.
- **Datastore provider** — collection-level Zod schemas, change-stream subscriptions, TTL indexes.
- **Skills** — Claude Code skills with tool whitelists and trigger-phrase manifests.
## Configuration
Configure via `~/.swamp/config.yaml` or environment variables. The full method reference and rubric format live in the package's `manual/` directory.
**Labels:** `evaluation` `ai`
linux-aarch64darwin-x86_64linux-x86_64darwin-aarch64
evaluationai
modelsdatastoresskills
1.0.1