name	implementation-logger
description	Log implementation decisions — tracks deviations from plan and captures rationale
license	MIT
compatibility	cline, claude, opencode, amp, codex, gemini, cursor, pi
hint	Use during implementation of complex or uncertain changes to track decisions
user-invocable	true

Implementation Logger

When to Use

Use this skill during implementation when:

Working on complex or uncertain changes
The implementation approach isn't fully defined
You want to track decisions for documentation
Building knowledge about unknowns for future work
Need to explain reasoning in PR descriptions

What It Does

Tracks deviations from the original plan and decision rationale during implementation. Helps identify where your mental model (map) differed from reality (territory).

How to Execute

Step 1: Set Up Logging

At the start of implementation, create a log file:

# Create implementation log
echo "# Implementation Log: [Feature Name]" > .implementation-log.md
echo "" >> .implementation-log.md
echo "Started: $(date)" >> .implementation-log.md
echo "" >> .implementation-log.md
echo "## Original Plan" >> .implementation-log.md
echo "[Brief summary of approach]" >> .implementation-log.md
echo "" >> .implementation-log.md
echo "## Deviations & Decisions" >> .implementation-log.md

Step 2: Log During Implementation

Whenever reality differs from plan, log it:

### [Timestamp] - [Decision Point Title]

**Context**: What I encountered that wasn't in the plan

**Original Assumption**: What I thought would work

**Reality**: What I actually found

**Decision**: What I decided to do instead

**Rationale**: Why this approach is better/necessary

**Impact**: What else this might affect

Step 3: Log Categories

Track different types of deviations:

Architectural Discoveries:

Found existing abstraction that changes approach
Realized need for new pattern
Dependency constraints

Unknown Unknowns:

Edge cases not in spec
Integration points discovered
Performance considerations

Technical Constraints:

Library limitations
Type system issues
Test infrastructure gaps

Spec Gaps:

Ambiguous requirements
Missing error handling specs
Unclear business logic

Step 4: Review & Extract

After implementation:

Review log for patterns
Extract key learnings for documentation
Identify knowledge to preserve
Update relevant docs/ADRs

Log Template

# Implementation Log: [Feature Name]

**Date**: [Date]
**Developer**: [Name or Agent ID]
**Original Plan**: [Link to spec/plan]

## Summary
[One paragraph: what we built and key decisions]

## Original Approach
[What we planned to do]

## Deviations & Decisions

### Decision 1: [Title]
**When**: [Timestamp/phase]
**Context**: [What prompted this decision]
**Original Plan**: [What we thought we'd do]
**Reality**: [What we actually found]
**Decision**: [What we decided]
**Rationale**: [Why this is better]
**Impact**: [Side effects or dependencies]
**Code**: [Link to relevant commit/files]

### Decision 2: [Title]
...

## Unknowns Discovered

### Unknown: [Title]
**Category**: [Architecture/Spec/Technical/Business]
**Impact**: [High/Medium/Low]
**Description**: [What we didn't know]
**Resolution**: [How we resolved it]
**Future Consideration**: [Should this inform future work?]

## Learnings

### What Worked Well
- [Learning 1]
- [Learning 2]

### What Was Surprising
- [Surprise 1]
- [Surprise 2]

### What to Do Differently Next Time
- [Improvement 1]
- [Improvement 2]

## Documentation Updates Needed
- [ ] Update ADR on [topic]
- [ ] Add to MEMORY.md: [learning]
- [ ] Update [skill/guide]: [improvement]

## Follow-up Questions
1. [Question that arose during implementation]
2. [Question for stakeholder/team]

Example Usage

# Implementation Log: GitHub OAuth Integration

**Date**: 2026-07-08
**Original Plan**: docs/specs/github-oauth.md

## Summary
Implemented GitHub OAuth provider following existing OAuth pattern.
Key deviation: Used App Installation flow instead of user OAuth due to
org-level permission requirements. Added webhook endpoint for
installation events.

## Original Approach
- Implement standard OAuth 2.0 flow via library
- Use Personal Access Token (PAT) flow for initial testing

## Deviations & Decisions

### Decision 1: Use GitHub App Installation Flow

**When**: During initial auth flow implementation

**Context**: Testing revealed that org-level repo access requires GitHub
App installation, not user OAuth. Our target users need org repo access.

**Original Plan**: Standard OAuth with PAT

**Reality**: GitHub deprecated PAT for org access. Apps must use
Installation flow which requires:
- App installation per organization
- Installation webhook handling
- Installation-specific tokens

**Decision**: Implement GitHub App Installation flow instead

**Rationale**:
- Only way to get org-level repo access
- More secure (granular permissions)
- Better aligned with GitHub's current best practices
- Matches what users expect (seen in other tools)

**Impact**:
- Added webhook endpoint: /webhooks/github/installation
- New database table: github_installations
- Installation token refresh logic (expires after 1hr vs 6mo)
- More complex setup docs (users must create GitHub App)

**Code**: commit abc123, files: auth/github/installation.ts

### Decision 2: Cache Installation Tokens

**When**: During token refresh implementation

**Context**: Installation tokens expire after 1 hour. Naive approach would
request new token for every API call.

**Original Plan**: Request new token on each API call

**Reality**: GitHub rate limits token requests to 5000/hour per app.
With multiple users in same org, we'd hit limit quickly.

**Decision**: Cache installation tokens in Redis with 55min TTL

**Rationale**:
- Prevents rate limit issues
- Reduces latency (no token request per API call)
- 55min TTL provides 5min safety buffer before expiry
- Existing Redis used for other caching

**Impact**:
- Added Redis key pattern: github:install:{id}:token
- Token refresh logic checks cache first
- Cache invalidation on installation webhook events

**Code**: commit def456, files: auth/github/token-cache.ts

### Decision 3: Handle Installation Deletion

**When**: Writing webhook handler

**Context**: Users can uninstall the GitHub App from their org

**Original Plan**: Not explicitly considered

**Reality**: Installation deletion is common (users test, revoke, etc).
Must handle gracefully.

**Decision**: Soft-delete installations, preserve audit log

**Rationale**:
- Maintain audit trail of access history
- Prevent orphaned references in user sessions
- Allow re-installation without data loss
- Compliance requirement (track who had access when)

**Impact**:
- Added `deleted_at` column to github_installations
- Webhook handler for installation.deleted event
- Session middleware checks installation.deleted_at
- User sees clear error: "GitHub integration removed"

**Code**: commit ghi789, files: webhooks/github.ts

## Unknowns Discovered

### Unknown: GitHub App vs OAuth App
**Category**: Architecture
**Impact**: High
**Description**: Didn't realize GitHub has two different app types with
different capabilities. OAuth Apps can't get org-level repo access.
**Resolution**: Used GitHub App with Installation flow
**Future Consideration**: Document this in our OAuth integration guide.
Other providers may have similar dual-model systems.

### Unknown: Installation Token Lifespan
**Category**: Technical
**Impact**: Medium
**Description**: Installation tokens expire after 1 hour, not 6 months
like user tokens. This wasn't in our initial spec.
**Resolution**: Implemented caching strategy
**Future Consideration**: Standard pattern for short-lived tokens?

### Unknown: Rate Limit on Token Requests
**Category**: Technical
**Impact**: Medium
**Description**: Token endpoint has its own rate limit separate from API
**Resolution**: Cache tokens in Redis
**Future Consideration**: Consider for other OAuth providers too

## Learnings

### What Worked Well
- Blind spot pass identified existing OAuth pattern to follow
- Webhook infrastructure was already in place
- Redis caching pattern from other auth providers was reusable

### What Was Surprising
- GitHub's dual app model (wasn't in initial research)
- How common installation deletion is (users test a lot)
- Token request rate limiting (separate from API limits)

### What to Do Differently Next Time
- Research provider-specific gotchas more deeply upfront
- Ask explicitly about token lifespan in spec interview
- Consider short-lived tokens in architecture discussions

## Documentation Updates Needed
- [x] Add to skills/blindspot-pass examples: Check for dual auth models
- [ ] Update MEMORY.md: GitHub Apps vs OAuth Apps distinction
- [ ] Create ADR: Short-lived token caching strategy
- [ ] Update OAuth integration guide with GitHub App specifics

## Follow-up Questions
1. Should we implement GitHub App for user-level access too (consistency)?
2. Do other OAuth providers have similar dual models to document?
3. Should Redis cache TTL be configurable per provider?

Best Practices

Log as you go: Record decisions throughout implementation
Be specific: Include timestamps, commit SHAs, file paths
Explain reasoning: Not just what changed, but why
Note impact: What else does this affect?
Extract learnings: Turn log into documentation
Keep it concise: Each entry should be 1-2 paragraphs max

Integration with Other Skills

Before Implementation: Blind spot pass + spec interview reduce unknowns
During Implementation: Use this skill to track deviations
After Implementation: Extract for PR description, ADRs, MEMORY.md
Follow-up: Quiz-me to verify you understand the logged decisions

Output Locations

Where to Store Logs

Temporary logs (during work):

.implementation-log.md  # Git ignored, working file

Permanent documentation (after completion):

docs/adr/NNN-[decision].md          # Architecture decisions
MEMORY.md                            # Gotchas and learnings
wiki/[topic]/[entry].md              # Knowledge base entries
.github/pull_requests/[PR].md        # PR description

Git Ignore

Add to .gitignore:

.implementation-log.md
.dev-notes.md

These are working files, not committed artifacts.

Success Criteria

A good implementation log:

Records at least 2-3 deviations from original plan
Explains rationale for each decision
Identifies unknowns discovered
Provides material for PR description
Takes minimal time to maintain (1-2 min per entry)
Results in better documentation

Common Pitfalls

Focus on decisions: Log only changes in direction and rationale
Too late: Logging after the fact loses context and rationale
No extraction: Log sits unused instead of feeding documentation
No patterns: Missing the forest for the trees; look for themes
Defensiveness: Log is for learning, not justifying; be honest

Advanced: Auto-logging

For advanced workflows, automatically log key events:

# Git commit hook to prompt for log entries
# .git/hooks/post-commit

#!/bin/bash
if [ -f .implementation-log.md ]; then
  echo "📝 Implementation log detected. Add entry for this commit? (y/n)"
  read -r response
  if [ "$response" = "y" ]; then
    echo "" >> .implementation-log.md
    echo "### $(date) - $(git log -1 --pretty=%B)" >> .implementation-log.md
    echo "**Commit**: $(git rev-parse --short HEAD)" >> .implementation-log.md
    echo "**Decision**: [TODO: Fill in]" >> .implementation-log.md
    echo "" >> .implementation-log.md
    echo "Log entry template added. Edit .implementation-log.md"
  fi
fi

This reminds you to log after each commit.