## Thinking Path
> - Paperclip is the open source control plane people use to manage
AI-agent companies and their work
> - Human approvals, issue interactions, and execution decisions already
capture high-value decision moments
> - Those moments are currently transient and cannot be reused as stable
evaluation or training examples
> - Reusable examples need a server-owned, immutable snapshot so later
comments or runs cannot leak into the recorded state
> - Human notes need to remain editable and auditable without changing
the captured state
> - This pull request adds the database model, snapshot capture service,
API, export format, and attention-feed enrichment for decision training
> - The benefit is a durable, inspectable foundation for evaluating
whether agents can reproduce good human decisions from only the context
available at decision time
## Linked Issues or Issue Description
### Subsystem affected
Cross-cutting (`server/`, `packages/db`, and `packages/shared`).
### Problem or motivation
Paperclip has no durable dataset for converting human decisions into
evaluation-ready examples. Teams need to capture pending or resolved
decisions with the exact issue context, comments, runs, and repository
evidence available at a cutoff, while preventing future context from
leaking into the example.
### Proposed solution
Store immutable, schema-versioned snapshots anchored to durable
interaction, approval, or execution-decision records; keep notes
separately editable with history; expose human-only CRUD, list, and
JSONL export APIs.
### Alternatives considered
Client-generated snapshots were rejected because they duplicate cutoff
logic and cannot reliably enforce no-leakage boundaries. Automatic
outcome backfill was deferred so captured examples remain faithful to
what was known at capture time.
### Roadmap alignment
Supports the roadmap direction of turning completed work and decision
patterns into reusable organizational knowledge.
### Additional context
The implementation records explicit commit-resolution confidence
(`exact`, `nearest_run`, `workspace`, or `none`) so downstream
evaluation can distinguish evidence quality.
## What Changed
- Added the `decision_training_examples` schema and idempotent migration
with company, issue, and source/author indexes.
- Added shared types for decision-training records, notes history, and
versioned snapshots.
- Added a single server-side snapshot capture path with inclusive
comment cutoffs, pre-cutoff run capture, durable decision payloads, and
explicit commit-resolution confidence.
- Added create, list, detail, notes-only update, delete, and JSONL
export routes with human-only write authorization and activity logging
that skips no-op note submissions.
- Added per-user `trainingExampleId` enrichment to attention items.
- Added focused embedded-Postgres tests for cutoff boundaries,
post-cutoff leakage, immutable snapshots, human-only writes, duplicate
prevention, notes history, attention enrichment, and export shape.
- Updated UI test and Storybook attention-item factories for the new
required `trainingExampleId` contract.
## Verification
- `pnpm exec vitest run server/src/__tests__/decision-training.test.ts`
— 10 tests passed.
- `pnpm --filter @paperclipai/db typecheck` — passed, including
migration numbering and safety checks.
- `pnpm --filter @paperclipai/shared typecheck` — passed.
- `pnpm --filter @paperclipai/server typecheck` — passed.
- `pnpm --filter @paperclipai/ui typecheck` — passed.
## Risks
- The migration adds a new table and indexes only; it does not rewrite
existing rows or install resolve-time hooks.
- Snapshot JSON can grow with long comment threads and run histories; v1
intentionally favors complete, inspectable examples over aggressive
truncation.
- Commit SHA resolution is evidence-based and records `exact`,
`nearest_run`, or `none` so downstream consumers can account for
confidence.
- The API is additive, but future UI work must continue to treat the
snapshot as immutable and use notes-only updates.
> For core feature work, check [`ROADMAP.md`](ROADMAP.md) first and
discuss it in `#dev` before opening the PR. Feature PRs that overlap
with planned core work may need to be redirected — check the roadmap
first. See `CONTRIBUTING.md`.
## Model Used
- OpenAI Codex using `gpt-5.3-codex`, with repository tool use, terminal
execution, and code-editing capabilities; context-window size is not
exposed by the runtime.
## Checklist
- [x] I have included a thinking path that traces from project context
to this change
- [x] I have specified the model used (with version and capability
details)
- [x] I have checked ROADMAP.md and confirmed this PR does not duplicate
planned core work
- [x] I have searched GitHub for duplicate or related PRs and linked
them above
- [x] I have either (a) linked existing issues with `Fixes: #` / `Closes
#` / `Refs #` OR (b) described the issue in-PR following the relevant
issue template
- [x] I have not referenced internal/instance-local Paperclip issues or
links (only public GitHub `#NNN` / `github.com/paperclipai/paperclip`
URLs)
- [x] My branch name describes the change (e.g. `docs/...`, `fix/...`)
and contains no internal Paperclip ticket id or instance-derived details
- [x] I have run tests locally and they pass
- [x] I have added or updated tests where applicable
- [x] I have updated relevant documentation to reflect my changes
- [x] I have considered and documented any risks above
- [ ] All Paperclip CI gates are green
- [ ] Greptile is 5/5 with no open P2s, recommendations, or follow-ups
- [x] I will address all Greptile and reviewer comments before
requesting merge
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Co-authored-by: Paperclip <noreply@paperclip.ing>
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