Change Init

change-init

What this skill does

Mine git history for Change Decision Records (ChDRs) — the why behind how the code came to be — and write them as draft records for human review.

A ChDR captures a decision that was made in the past and survives only in commits + linked issue trackers:

• Scan a window of git log for commit messages that reference an issue tracker (JIRA keys, GitHub/GitLab #NNN, MR !NNN, or issue URLs)
• Cluster commits sharing one issue key into a single change story
• Best-effort fetch the issue title/body (GitLab via MCP, GitHub via gh, else link-only) for requirement-level context
• Infer the Decision from the diff summary; record Consequences (reverts, follow-up fix chains — the negative knowledge almost never documented elsewhere)
• Write ChDR-{NNN}.md to {REPO_ROOT}/.adlc/drafts/chdr/ with status Discovered
• Regenerate {REPO_ROOT}/.adlc/drafts/chdr/chdr.md index

Key differences from the team-levelup family:

ChDRs are project-local memory (this repo's evolution), not team-wide context — they fail the team-levelup "team-wide applicability" signal gate. They publish to {REPO_ROOT}/docs/adlc/memory/chdr/ (see /change-publish), and their index is injected at session start by team-boot.

When to use

Note: Class boots detect in-session change rationale and suggest /change-specify (which writes the lightweight draft to .adlc/drafts/). This skill is for interactive deep-dive exploration — guided history mining, change-story clustering, and rationale recovery before documenting.

• Brownfield onboarding: give an agent project memory without anyone writing docs
• Before refactoring unfamiliar code: surface Chesterton's fences — constraints that exist only in old commits + tickets
• Recovering lost rationale: when ADRs were never written but commits + issues exist
• Post-incident learning: revert/fix chains are first-class output

When NOT to use

• Greenfield / no history: nothing to mine
• Documenting current patterns: use /team-init (what IS)
• Capturing this session's learnings: use /team-levelup
• Capturing this session's change rationale: use /change-specify
• Pending ChDRs already exist: run /change-clarify to review them first

Process

User Input

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$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Examples of User Input:

• "--since 6months" — limit the scan window
• "--tracker gitlab" — force tracker type (auto by default)
• "--no-fetch" — record issue links only, never fetch issue bodies
• "--include-unlinked" — also surface signal-rich unlinked commits (reverts, large cross-cutting diffs)
• "src/payments" — restrict to a path
• Empty input: scan last 500 commits across the whole repo, auto-detect tracker

Flags

• --since DATE / --until DATE / --max-count N (default 500): git log windowing
• --path PATH: restrict to a pathspec
• --tracker gitlab|github|jira|auto (default auto): issue-tracker integration
• --no-fetch: detect+record issue links only, never fetch bodies
• --include-unlinked: also cluster signal-rich unlinked commits (reverts, diffs touching ≥3 subsystems)
• --limit N (default 20): cap number of ChDRs generated
• --resume: resume from previous interrupted state

Role & Context

You are a Context Archaeologist recovering why the code is the way it is. Your job is inference from evidence, not invention:

• Every Decision claim MUST cite the commit SHA(s) and/or issue URL it was inferred from (provenance is non-negotiable — an unprovenanced inferred rationale is context poisoning, worse than no rationale)
• Mark confidence (HIGH/MEDIUM/LOW) on each Decision
• Record what you do NOT know explicitly ("Reason for choice unknown — commit message terse, no linked issue")
• Reverts and follow-up fix chains are the highest-value content: they are negative knowledge ("we tried X, it broke Y") documented almost nowhere else

Outline

1. Validate Environment (Phase 1): git repo, resolve paths, next ChDR number
2. Scan Window (Phase 2): git log with windowing
3. Detect Issue Links (Phase 3): regex over commit messages
4. Cluster into Change Stories (Phase 4): group commits by issue key
5. Best-Effort Issue Fetch (Phase 5): tracker content (degrade gracefully)
6. Detect Revert/Fix Chains (Phase 6): first-class negative knowledge
7. Score & Prioritize (Phase 7): subsystems touched, diff size, chains
8. Generate ChDRs (Phase 8): write drafts + index
9. Output (Phase 9): summary with linkage-rate metric

Execution Steps

Phase 1: Validate Environment

Run the setup script from the skill's base directory:

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scripts/bash/setup-change-init.sh

Parse the JSON output for REPO_ROOT, CHDR_DRAFTS_DIR, NEXT_CHDR, GIT_AVAILABLE, DEFAULT_BRANCH, TD_CONFIGURED, EXISTING_CHDRS.

If the setup script is unavailable or fails, resolve manually:

1. REPO_ROOT — walk up from cwd to find .adlc/, or git rev-parse --show-toplevel, or pwd.
2. CHDR_DRAFTS_DIR — REPO_ROOT/.adlc/drafts/chdr
3. NEXT_CHDR — list CHDR_DRAFTS_DIR/ChDR-*.md, find highest number, increment, zero-pad to 3 digits.
4. GIT_AVAILABLE — git rev-parse --is-inside-work-tree (exit 0 = true).
5. TD_CONFIGURED — true if TEAM_AI_DIRECTIVES resolves (used only to skip duplicate decisions already captured as CDRs).

If GIT_AVAILABLE is false:

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Not a git repository — change-init has nothing to mine.
Run /team-init to scan current code instead.

Exit cleanly (do not create empty drafts).

Phase 2: Scan Window

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git log --pretty=format:'%H%x09%an%x09%ad%x09%s%n%b' --date=short \
  ${SINCE:+--since="$SINCE"} ${UNTIL:+--until="$UNTIL"} --max-count="${MAX_COUNT:-500}" \
  ${PATHSPEC:+-- "$PATHSPEC"} 2>/dev/null

Capture per commit: SHA, author, date, subject, body, files touched (git show --stat --name-only), and subsystems (top-level dirs of touched files).

Phase 3: Detect Issue Links

Apply a combined regex to each commit message (subject + body):

Tracker type is auto-inferred from git remote get-url origin (gitlab.com / github.com / atlassian.net) and the link shapes found. --tracker overrides.

Commits with no detected link are unlinked; skipped unless --include-unlinked (then only those that are reverts or touch ≥3 subsystems are kept).

Phase 4: Cluster into Change Stories

Group commits by issue key. One issue key → one candidate ChDR. For URL-only links, normalize to the issue number. Merge subject + body text across the cluster as the raw rationale corpus.

Phase 5: Best-Effort Issue Fetch

For each cluster, fetch the issue title + body summary as Context (the requirement that motivated the change). Best-effort, never blocking:

• GitLab: use the configured GitLab MCP tools (gitlab_get_issue by project+iid). If unavailable, try glab issue view.
• GitHub: gh issue view <num> --json title,body (if gh is authenticated).
• JIRA / unreachable: link-only — record the URL as evidence, Context comes from commit messages alone.

--no-fetch skips this phase entirely. Any fetch failure degrades to commit-message context (do not abort).

Security: issue bodies may contain sensitive detail. Summarize the requirement in 1-3 sentences; do not paste raw issue bodies verbatim into the ChDR. The human gate (/change-clarify) reviews before promotion.

Phase 6: Detect Revert/Fix Chains (first-class)

Across the whole window (independent of issue links):

• Reverts: git log --grep='^Revert "' --pretty=format:'%H %s' and git log --grep='revert' -i. For each reverted original commit, record it as negative knowledge.
• Fix chains: commits whose subject matches fix(?!ed)?\b or hotfix that touch the same files as an earlier commit in the window — a follow-up fixing a regression. Record the pair (original, fix) as a consequence.

Reverts and fix chains that have no issue link are still captured when --include-unlinked is set (they are the highest-value unlinked signal). When a revert/fix chain belongs to an issue-linked cluster, attach it to that cluster's ### Consequences.

Phase 7: Score & Prioritize

Score each candidate (0.0–1.0):

• subsystems touched (cross-cutting = higher)
• diff size (larger = higher, capped)
• has revert/fix-chain consequence (boost — negative knowledge)
• has fetched issue context (boost — richer rationale)
• recency (mild boost)

Sort descending; take top --limit (default 20). Skip candidates with score below 0.2 (trivial).

Phase 8: Generate ChDRs

For each selected change story, write {CHDR_DRAFTS_DIR}/ChDR-{NNN}.md:

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## ChDR-NNN: [Title — from issue title or commit subject]

### Status: **Discovered**

### Date: [YYYY-MM-DD of most recent commit in cluster]

### Source: Git history via /change-init

### Issue Links: [keys/URLs, or "none detected"]

### Commits: [sha list, abbreviated]

### Target Module: `docs/adlc/memory/chdr/[slug].md`

### Descriptor: One-line "when to consult this" summary for the chdr.md index.

### Context
[Why the change was made — issue title/body summary (1-3 sentences) + commit messages. Cite SHAs inline.]

### Decision
[What was decided/implemented — inferred from diffs. Mark confidence: HIGH/MEDIUM/LOW. Each claim cites its SHA/URL.]

### Consequences
[Reverts, follow-up fix chains, later modifications — negative knowledge. "None observed" if the cluster has no reversals.]

### Evidence
- `{sha}`: {commit subject}
- {file/path}: {what changed}
- {issue-url}: {title} (fetched | link-only)

Rules:

• Every ### Decision claim cites a SHA or URL (provenance — the context-poisoning circuit breaker).
• "Reason unknown" is acceptable and preferred over invention.
• Confidence is mandatory on Decision claims.

Then regenerate {CHDR_DRAFTS_DIR}/chdr.md index by listing all ChDR-*.md files and building a markdown table from their single-line fields:

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# Change Decision Records (Drafts)

## ChDR Index

| ID | Status | Date | Issues | Commits | Descriptor |
|----|--------|------|--------|---------|------------|
| ChDR-001 | Discovered | 2026-08-16 | PROJ-123 | abc1234 | Why payments retries are capped at 3 |

**Stats**: N entries | Last Updated: YYYY-MM-DD

Phase 9: Output Summary

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## Change-Init Summary

- Scan window: [since/until or "last N commits"]
- Commits scanned: N
- Issue-linked commits: M (linkage rate: P%)
- Clusters formed: K
- Revert/fix chains detected: C
- ChDRs generated: N (capped at --limit)
- Output: `{REPO_ROOT}/.adlc/drafts/chdr/`

Linkage rate sets expectations about corpus quality (research shows rationale density varies widely by team discipline — 85–99% on disciplined projects like the Linux kernel, far lower elsewhere). Below ~30%, suggest --include-unlinked for the next run.

Key Rules

Evidence-Based, Never Fabricated

• Only document decisions inferable from commits + issues
• Cite specific SHAs and/or issue URLs on every Decision claim
• Mark confidence levels (HIGH/MEDIUM/LOW)
• "Reason unknown" is acceptable; invention is not

Non-Destructive

• Do not overwrite existing ChDRs without approval
• Preserve manually added content
• Merge intelligently if a ChDR already exists for the same issue key

Graceful Degradation

• Not a git repo → exit cleanly, no empty drafts
• Tracker unreachable → link-only evidence, proceed
• Empty/terse commit messages → rely on diffs + issue fetch; if both absent, skip the cluster

No Fabricated Rejection Rationale

• For inferred decisions, use neutral "Observed Alternatives" framing
• "We don't know why X wasn't chosen" is acceptable

Workflow Guidance & Transitions

After /change-init

Required: Run /change-clarify to validate discovered ChDRs.

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/change-init
    ↓
[Mine git history] → Detect issue links, cluster, infer decisions
    ↓
[Generate ChDRs] → Write to .adlc/drafts/chdr/ChDR-{NNN}.md (Discovered)
    ↓
[Run /change-clarify] → Validate and accept/reject ChDRs
    ↓
[Run /change-publish] → Promote accepted ChDRs to docs/adlc/memory/chdr/
    ↓
[team-boot] → Injects docs/adlc/memory/chdr/chdr.md index at next session start

Next Steps

After init completes, run /change-clarify to refine and validate the discovered ChDRs.

Verification

• ChDRs written to {REPO_ROOT}/.adlc/drafts/chdr/ChDR-{NNN}.md with status Discovered.
• Auto-generated chdr.md index exists in {REPO_ROOT}/.adlc/drafts/chdr/.
• Every ChDR's ### Decision claims cite at least one SHA or issue URL (provenance).
• Revert/fix chains detected in the window appear in ### Consequences (or "None observed").
• Linkage-rate metric appears in the summary.
• No existing ChDRs were overwritten without explicit approval.

Context

$ARGUMENTS