Objective

Reconstruct Architecture Decision Records from a repository's git history and documentation. You're doing archaeology — finding the decisions buried in commits, specs, and docs, then surfacing them as ADRs.

An ADR is warranted when someone made a choice that shaped the system. Not every commit is a decision. Your job is to find the ones that were.

Process

1. Classify files — Distinguish architectural files (where decisions manifest) from supportive files (tests, utils). Persist this classification.
2. Identify candidate commits — Find commits that touch architectural files with structural changes (not just edits).
3. Cluster into decisions — Group related commits that represent a single decision being implemented.
4. Fill gaps — Pull in minor commits (typo fixes, forgotten files) that belong to a cluster but were filtered out.
5. For each cluster — Analyze intent, ask the user for context, generate the ADR.
6. Scan complementary sources — Check specs/ and docs/ for decisions not captured by commits.
7. Enrich ADRs — Add cross-references, diagrams, and implementation notes from related documentation.
8. Order chronologically — Renumber ADRs to maintain chronological sequence.
9. Update ADR index — Keep specs/architecture/ADR/README.md in sync after any ADR is added, removed, or renumbered.

Maintain state in files so work isn't lost if the conversation ends.

1. File Classification

Consider all files - present and deleted. Deletion may reveal an architectural decision.

Architectural (decisions live here)

Tier 0 — Dependency manifests (highest signal)

• requirements.txt, pyproject.toml, package.json, go.mod, Cargo.toml
• Every addition/removal is a technology choice

Tier 1 — Infrastructure & deployment

• Dockerfile, docker-compose*.yml, CI configs, terraform, k8s manifests
• How the system runs and deploys

Tier 2 — Domain structure

• Core modules, domain boundaries, entry points, service definitions
• The shape of the system

Tier 3 — Interface contracts

• OpenAPI specs, protobuf, GraphQL schemas, API route definitions
• Commitments to the outside world

Supportive (usually not decisions)

• Tests, utils/helpers, generated files, migrations, dev tooling, config instances

Decision artifacts (check separately)

• specs/ — Design documents that may contain decisions preceding implementation
• docs/ — Usage guides and criteria that may encode decisions-as-code

Judgment calls

Some files blur the line. When uncertain, ask: "If this changed significantly, would a senior engineer want to know why before approving?" If yes, it's architectural.

2. Structural Change Signals

Not every change to an architectural file is a decision. Look for:

• New directory created
• File renamed or moved (especially across boundaries)
• Dependency added, removed, or major-version bumped
• New entry point (CLI command, API route, service)
• CI/CD pipeline added or significantly changed
• New base class or interface that others will inherit/implement
• Configuration schema change (not just values)

A 200-line refactor in a util is less ADR-worthy than a one-line addition of celery to requirements.txt.

3. Clustering

What makes a good cluster

• Represents ONE decision, even if implemented across multiple commits
• Commits are related by intent, not just proximity
• Typically spans days to a couple weeks, not months
• Has a name you could say in a sentence: "the Celery migration", "switching to FastAPI"

When to break clusters

• Large time gap (>1-2 weeks) with context switch
• Different author working on unrelated area
• Explicit markers: "BREAKING", "v2", "rewrite", "migrate to X"

Candidate numbering

Assign candidate numbers in strict chronological order (earliest commit date first). This numbering carries through to the final ADR sequence ID. When presenting candidates grouped by confidence tier, sort candidates within each group by ascending number (i.e. chronologically).

Anti-patterns

• Over-clustering: One giant cluster called "backend infrastructure" — too broad
• Under-clustering: Every commit is its own cluster — too granular
• Mixing decisions: Celery integration + unrelated API redesign in one cluster

When uncertain about boundaries, ask the user.

4. Gates (when to stop and ask)

Classification ambiguity

"I'm unsure whether src/lib/kafka_client.py is architectural (core infrastructure) or supportive (utility). It's used by 12 services. How do you see it?"

Cluster boundaries

"Commits abc123–def456 span 3 weeks and touch both the new auth system and the database migration. Should these be one decision or two?"

Intent unclear

"This cluster adds Redis, but I can't tell if it's for caching, session storage, or as a Celery broker. What was the driver?"

Low confidence

"I found 4 commits that add logging configuration. Is this ADR-worthy or just housekeeping?"

Always ask before generating an ADR. Present your analysis, let the user confirm or correct.

5. User Context to Gather

Before generating each ADR, ask for:

1. Trigger — What problem or constraint forced this decision?
2. Alternatives — What else was considered?
3. Rationale — Why this solution over the alternatives?
4. Tradeoffs accepted — Known limitations, risks, or debt?
5. Related decisions — Does this supersede or depend on other ADRs?

If PR descriptions or commit messages already contain this, confirm rather than re-ask.

6. Complementary Sources

Git commits are the primary source but not the only one. Some decisions are better documented in specs or docs than in commit messages.

Specs as decision artifacts

Check specs/ for:

• Design documents that preceded implementation
• Decision specs that explain why before what
• Technical specifications that represent architectural choices

A spec file often documents a decision that spans multiple commits or was made before coding began. When you find a spec that describes a decision:

1. Note it as a potential ADR source
2. Cross-reference with commits that implemented it
3. The spec becomes the "Considered Options" and "Rationale" section

Example: specs/platform-detection.md documented the three-module detection architecture before implementation — this warranted its own ADR even without a clear commit cluster.

Docs as enrichment sources

Check docs/ for:

• Usage guides that reveal workflow decisions
• Selection criteria that encode preferences-as-code
• Architecture overviews that contextualize other decisions

Docs may not warrant their own ADR but can enrich commit-based ADRs with:

• Pipeline diagrams and data flow
• Scoring systems and thresholds
• Integration points between components

Example: docs/SELECTION-CRITERIA.md documented the scoring system as a deliberate choice — this warranted an ADR capturing the "criteria as code" decision.

Gap analysis workflow

After generating commit-based ADRs:

1. Read all specs and docs — Identify significant decisions not yet captured
2. Present gaps to user — "I found N decisions in specs/docs not covered by commit-based ADRs"
3. Generate supplementary ADRs — Mark source as spec/doc rather than commits

Gate:

"I found these decisions in specs/docs that aren't captured by commit-based ADRs:

1. Platform detection architecture (specs/platform-detection.md)
2. Sector taxonomy resolution (specs/sector-taxonomy.md) Which should become ADRs?"

7. ADR Enrichment

After initial ADR generation, enrich with cross-references and context from related documentation.

Cross-reference mapping

Build a reference graph:

• Which ADRs depend on prior decisions?
• Which ADRs supersede or extend others?
• Which ADRs are implemented together?

Use explicit references: "With the ATS extractor architecture established (ADR-0003, ADR-0008)..."

Enrichment from related docs

For each ADR, check if related docs contain:

• Diagrams that clarify architecture (pipeline flows, module relationships)
• Tables that summarize implementation details (platform coverage, scoring weights)
• Workflows that show how components interact

Add these as inline content within relevant sections, not just as references.

Example enrichment:

### Architecture

**6-Phase Pipeline Vision** (designed from day one):
\`\`\`
Phase 0: Company Discovery    → company-inventory.md
Phase 1: Job Discovery        → career_jobs/*.json
...
\`\`\`

Implementation Notes section

When the user provides collaboration context, add an "Implementation Notes" section capturing:

• Collaboration patterns — How human and AI worked together
• Technical decisions — Choices made during implementation
• Technical debt — Issues identified post-implementation

Example:

### Implementation Notes

**Collaboration model:** Paired with Claude on specs, implementation, and tests.
Human wrote ~20 LoC to demonstrate the `@register_extractor` decorator mechanism
and the base class pattern — faster than explaining. Every line reviewed with
many requested changes.

**Subsequent findings:** Architecture review identified technical debt:
- REQUEST_TIMEOUT duplication (10+ files, values 10-30s)
- Intra-module duplication in `extract_job_listings.py`

8. Chronological Ordering

ADRs should be numbered chronologically by decision date, not generation order.

When supplementary ADRs are added

If spec-derived ADRs fall chronologically between commit-based ADRs:

1. Build chronological mapping — Order all ADRs by date (commit dates or spec creation dates)
2. Propose renumbering — Show old→new mapping to user for approval
3. Execute with git mv — Use git mv for rename tracking
4. Update content:
   • Title headers (# 15 - ... → # 2 - ...)
   • Cross-references (ADR-0005 → ADR-0008)
   • State file with new paths

Renaming strategy

To avoid conflicts when numbers swap:

1. Rename all changing files to temp names (git mv 0002-*.md temp-0002-*.md)
2. Rename from temp to final names (git mv temp-0015-*.md 0002-*.md)

Ordering criteria

1. Commit date range — Earliest commit in cluster
2. Spec creation date — From git log of spec file
3. Logical dependency — If A depends on B, B comes first

9. ADR Output

Use MADR format unless the user specifies otherwise. Place in specs/architecture/ADR/ or the project's existing ADR location.

Footer for commit-based ADRs

---
*Reconstructed from commits {first_sha}..{last_sha} ({date_range})*

Footer for spec/doc-derived ADRs

---
*Reconstructed from {source_file} ({date_range})*

9. ADR Index Maintenance

After generating, renumbering, or removing ADRs, update specs/architecture/ADR/README.md.

The index is a markdown table with two columns: ADR (linked title) and Decision (one-sentence outcome).

• Add a row for each new ADR with a relative link and a one-sentence summary of the decision outcome.
• Renumber rows when ADRs are reordered (step 8).
• Remove rows for deleted or superseded ADRs.
• Keep rows sorted by ADR number (ascending).

Quality Bar

A good backfilled ADR:

• Could have been written at the time of the decision
• Captures why, not just what
• Stands alone (reader doesn't need to grep the codebase)
• Is honest about what's reconstructed vs. confirmed by the user
• Cross-references related ADRs appropriately
• Includes enrichment from specs/docs where relevant

A bad backfilled ADR:

• Just describes the code changes
• Invents rationale that the user didn't confirm
• Combines multiple unrelated decisions
• Misses the actual decision (documents a symptom, not the choice)
• Ignores relevant context in specs/docs

State Management

Persist your work so it survives conversation boundaries:

• specs/architecture/ADR/adr-backfill-state.yml — classification, clusters, processing progress
• specs/architecture/ADR/adr-backfill-clusters/ — one file per cluster with analysis and user input

Check for existing state at the start. Offer to resume or restart.

Anti-patterns to Avoid

• Inventing rationale: If you don't know why, ask. Don't fabricate.
• Over-automation: This is archaeology, not manufacturing. User judgment is essential.
• Boiling the ocean: Start with high-confidence clusters (tier 0-1 changes). Get feedback. Calibrate.
• Treating all commits equally: A dependency addition is almost always a decision. A whitespace fix never is.
• Ignoring specs/docs: Commits are primary but not exclusive. Decisions often exist in documentation first.
• Skipping enrichment: A bare ADR is less useful than one with diagrams, tables, and cross-references.

Getting Started

When the user invokes this skill:

1. Check for existing state, offer to resume
2. If starting fresh, begin with file classification
3. Show the user your classification of tier 0-1 files for validation
4. Proceed through the process, asking at each gate
5. Number candidates chronologically (by earliest commit date); present grouped by confidence tier, sorted by ascending number within each group
6. After commit-based ADRs, scan specs/docs for gaps
7. Enrich ADRs with cross-references and context
8. Propose chronological renumbering if needed
9. Update specs/architecture/ADR/README.md index

Reference

State schema

# adr-backfill-state.yml
version: 1
repository: "git@github.com:org/repo.git"
started_at: "2024-01-15T10:30:00Z"
last_updated: "2024-01-15T14:22:00Z"

file_classification:
  # path → {tier: int | null, category: string, override: bool}
  "requirements.txt": {tier: 0, category: "dependency_manifest"}
  "src/core/domain.py": {tier: 2, category: "domain_structure"}
  "tests/test_domain.py": {tier: null, category: "test"}

commits:
  # sha → annotation
  "abc123":
    pruned: false
    highest_tier: 0
    signals:
      - {type: "dependency_added", weight: 1.0, details: {package: "celery"}}
    architectural_files: ["requirements.txt"]
    processed: true
  "def456":
    pruned: true
    processed: true

clusters:
  # Commit-based cluster
  - id: 17
    title: "Celery Integration"
    commit_shas: ["abc123", "abc124", "abc125"]
    gap_commits: ["abc123a"]
    date_range: "2024-01-10 to 2024-01-12"
    confidence: 0.85
    status: "adr_generated"  # pending | analyzed | user_enriched | adr_generated | skipped
    analysis:
      intent_hypothesis: "Introduce async task processing"
      solution_detected: "Celery with Redis broker"
    pr_metadata:
      number: 142
      title: "Add background job processing"
      description: "..."
    user_context:
      problem: "Synchronous email sending was blocking requests..."
      alternatives: "RQ, Dramatiq, custom threading"
      rationale: "Celery has best ecosystem support..."
      limitations: "Redis becomes SPOF..."
    adr_path: "specs/architecture/ADR/0017-celery-integration.md"

  # Spec/doc-derived cluster (supplementary ADR)
  - id: 18
    title: "Platform Detection Architecture"
    commit_shas: []  # Empty for spec-derived ADRs
    source: "specs/platform-detection.md"  # Source file instead of commits
    date_range: "2024-01-08 to 2024-01-15"
    confidence: 0.9
    status: "adr_generated"
    analysis:
      intent_hypothesis: "Design comprehensive ATS detection system"
      solution_detected: "Three-module architecture with fallback strategies"
    adr_path: "specs/architecture/ADR/0012-platform-detection-architecture.md"

processing_cursor:
  step: "cluster_analysis"  # classification | pruning | filtering | clustering | gap_filling | cluster_analysis | gap_analysis | enrichment | ordering
  cluster_index: 17
  substep: "user_enrichment"

configuration:
  max_time_gap_days: 7
  adr_output_dir: "specs/architecture/ADR"
  adr_format: "madr"  # madr | nygard | custom
  git_remote: "origin"
  pr_platform: "github"  # github | gitlab | bitbucket | none

MADR template

# [seq id] - [title]

## Context and Problem Statement

...

## Considered Options

1. [option name] - [description]
2. [option name] - [description]

## Decision Outcome

Chose **Option N**: ...

### Architecture

[diagrams, tables, module descriptions from enrichment]

### Rationale

...

### Implementation Notes

[collaboration patterns, technical decisions, debt identified — when provided by user]

### Consequences

**Positive:**
- ...

**Limitations accepted:**
- ...

---
*Reconstructed from commits {first_sha}..{last_sha} ({date_range})*