Skill

aidlc-outcomes-pack

Name: aidlc-outcomes-pack
Author: AWS Labs

generate AI-DLC workflow handover documentation

Published by AWS Labs Updated Sep 2

Covers Reporting Process Documentation Documentation

Description

Generate a comprehensive handover document at workflow close so the team can own, operate, and continue the system without re-running the workflow. Stage/phase/learning counts come from `aidlc-runtime.ts summary`; prose comes from the artefacts. Writes OUTCOMES.md but never mutates workflow state or emits audit events.

SKILL.md

AI-DLC Outcomes Pack

Purpose

Produce a single handover document at the close of a workflow that gives the team everything they need to own, operate, and keep building the delivered system — without re-running the workflow to recover context.

Classification

Read-only with respect to workflow state. This skill never advances the stage pointer and never emits an audit event. It does write one report artefact (OUTCOMES.md at the workspace root) — that is its output. It writes nothing else.

The counting rule

Stage tallies, per-phase rollup, memory-entry counts, and learnings captured come from the tool, not from eyeballing the artefact tree:

bun {{HARNESS_DIR}}/tools/aidlc-runtime.ts summary --json

Section content (what was built, setup steps, decisions) is yours to synthesise from the artefacts and the delivered code. Any count that appears in the pack must trace to the tool's output.

Steps

Step 1: Read the aggregates

Run bun {{HARNESS_DIR}}/tools/aidlc-runtime.ts summary --json.

If it exits non-zero (no runtime-graph.json yet), print:

No session data yet — an outcomes pack is generated at the close of a
workflow. Run /aidlc to completion first.

and STOP. Otherwise keep the parsed JSON for the count fields below.

Step 2: Read the content sources

Resolve <active-space> from aidlc/active-space (default default) and <active-intent> from aidlc/spaces/<active-space>/intents/active-intent. The active workflow record is aidlc/spaces/<active-space>/intents/<active-intent>.

All artefacts recursively under <record>/<phase>/ — requirements, design decisions, NFRs, infrastructure, and per-unit outputs.
The delivered application and infrastructure code at the workspace root.

Step 3: Write OUTCOMES.md

Write OUTCOMES.md at the workspace root (outside <record>/):

# Outcomes Pack
**Scope**: {summary.scope}
**Stages delivered**: {summary.stages.approved} approved / {summary.stages.total} total
**Duration**: {summary.duration_minutes} min

## 1. What Was Built
- Project name and description (from requirements)
- Scope the workflow ran at
- Units of work delivered and what each contains
- Key architectural decisions and why (from design artefacts)
- Tech stack with version pins

## 2. Repository Structure
- Annotated directory tree of the delivered code
- What lives where and why

## 3. Setup Guide
- Prerequisites (runtimes, tools, cloud CLI versions)
- Local development setup, step by step
- Required environment variables
- How to run tests

## 4. Build and Deploy
- Build steps
- Full test-suite run
- Infrastructure deployment (from Build and Test artefacts)
- IaC deployment commands with expected outputs, if generated

## 5. Architecture Decisions
- Every significant decision made during the workflow
- Alternatives considered and why rejected
- Constraints that shaped the design (from rules and practices)

## 6. What to Commit vs Archive
| Artifact | Action | Destination |
|----------|--------|-------------|
| `decisions.md` (per stage) | Commit | `docs/decisions/` |
| Architecture summary (1 page) | Write + commit | `docs/architecture.md` |
| NFR summary table | Write + commit | `docs/nfr-summary.md` |
| `<record>/audit/*.md` shards | Archive — do NOT commit to app repo | Compliance archive |
| Stage question files | Discard | — |
| `<record>/aidlc-state.md` | Discard | — |
| Application / infrastructure code | Already committed | — |

## 7. Workflow Footprint
- Stages: {summary.stages.approved} approved, {summary.stages.failed} failed, {summary.stages.pending} pending
- Memory entries captured: {summary.memory.total}
  ({summary.memory.interpretations} interpretations, {summary.memory.deviations} deviations, {summary.memory.tradeoffs} trade-offs, {summary.memory.open_questions} open questions)
- Learnings captured: {summary.learnings.from_orchestrator} from orchestrator, {summary.learnings.from_user_addition} from user additions

## 8. Known Limitations and What to Tackle Next
- Scope items explicitly deferred during the workflow
  (cross-reference the {summary.memory.open_questions} open questions above)
- Technical debt identified but not resolved
- Recommended next steps

Step 4: Confirm

Print a short summary: sections written, any sections skipped for missing source material, and recommended additions. You may offer one round of "want to add or adjust a section?" — do not loop on it.

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