5fea49b7c0
- Transform tufte-press from reference guide to conversation-aware generator - Add JSON generation from conversation context following strict schema - Create build automation scripts with Nix environment handling - Integrate CUPS printing with duplex support - Add comprehensive workflow documentation Scripts added: - skills/tufte-press/scripts/generate-and-build.sh (242 lines) - skills/tufte-press/scripts/build-card.sh (23 lines) Documentation: - Updated SKILL.md with complete workflow instructions (370 lines) - Updated README.md with usage examples (340 lines) - Created SKILL-DEVELOPMENT-STRATEGY-tufte-press.md (450 lines) - Added worklog: 2025-11-10-tufte-press-skill-evolution.org Features: - Agent generates valid JSON from conversation - Schema validation before build (catches errors early) - Automatic Nix shell entry for dependencies - PDF build via tufte-press toolchain - Optional print with duplex support - Self-contained margin notes enforced - Complete end-to-end testing Workflow: Conversation → JSON → Validate → Build → Print Related: niri-window-capture, screenshot-latest, worklog skills
256 lines
8.2 KiB
Markdown
256 lines
8.2 KiB
Markdown
# Feature 001: Screenshot Analysis - Resolution
|
||
|
||
**Status**: ✅ IMPLEMENTED (Minimal Viable Version)
|
||
**Location**: `skills/screenshot-latest/`
|
||
**Implementation Date**: 2025-11-08
|
||
|
||
## What We Built
|
||
|
||
A minimal skill that finds the most recent screenshot automatically so users don't have to type paths.
|
||
|
||
**Files created**:
|
||
- `skills/screenshot-latest/SKILL.md` - Agent instructions (83 lines)
|
||
- `skills/screenshot-latest/scripts/find-latest.sh` - Bash script (22 lines)
|
||
- `skills/screenshot-latest/README.md` - User documentation
|
||
- `skills/screenshot-latest/examples/example-output.txt` - Example output
|
||
|
||
**Total implementation**: 185 lines (including documentation)
|
||
|
||
## Usage
|
||
|
||
**User**: "Look at my last screenshot"
|
||
**AI**: <runs script> → <finds `/home/user/Pictures/Screenshots/Screenshot-2025-11-08-14-06-33.png`> → <analyzes image>
|
||
|
||
## What We Learned
|
||
|
||
### The Over-Engineering Journey
|
||
|
||
1. **Initial spec**: 635 lines of planning for 22 lines of code
|
||
2. **Task breakdown**: 82 tasks to implement 1 bash script
|
||
3. **Reality check**: `ls -t ~/Pictures/Screenshots/*.png | head -1` already works
|
||
4. **Reset**: Built minimal version in 22 minutes instead of implementing 82 tasks
|
||
|
||
**Key insight**: Specification time (115 min) vs Implementation time (22 min) = 5.2x waste
|
||
|
||
### Root Causes
|
||
|
||
1. **Template-driven development**: Filled in specification template without questioning scope
|
||
2. **Solution-first thinking**: Designed before coding
|
||
3. **Over-engineering bias**: Added features user didn't request
|
||
4. **Lost sight of value**: Built framework instead of solving problem
|
||
|
||
### What We Should Have Done
|
||
|
||
```bash
|
||
# Step 1: Test if problem is real (5 seconds)
|
||
ls -t ~/Pictures/Screenshots/*.png | head -1
|
||
|
||
# Step 2: It works? Ship it with docs (22 minutes)
|
||
echo "#!/bin/bash" > find-latest.sh
|
||
echo "ls -t ~/Pictures/Screenshots/*.{png,jpg,jpeg} | head -1" >> find-latest.sh
|
||
|
||
# Step 3: Done
|
||
```
|
||
|
||
## Scope Decisions
|
||
|
||
### What We Implemented (P1)
|
||
- ✅ Find latest screenshot by modification time
|
||
- ✅ Clear error messages (directory missing, no files)
|
||
- ✅ Support PNG, JPG, JPEG formats
|
||
- ✅ Fast execution (<1 second)
|
||
- ✅ Natural language triggers ("look at my screenshot")
|
||
|
||
### What We Deferred (P2-P3)
|
||
- ⏸️ Custom directories (YAGNI - default works for 95% of users)
|
||
- ⏸️ Nth screenshot lookup (YAGNI - not requested)
|
||
- ⏸️ Time-based filtering (YAGNI - not requested)
|
||
- ⏸️ Configuration files (YAGNI - hardcoded path is fine)
|
||
- ⏸️ Symlink handling (YAGNI - not mentioned in original request)
|
||
|
||
### Future Enhancements (If Requested)
|
||
|
||
**File-based improvements**:
|
||
- Support custom screenshot directories
|
||
- Find "second-to-last" or Nth screenshot
|
||
- Time-based filtering ("screenshot from 5 minutes ago")
|
||
|
||
**Direct capture approach** (more interesting):
|
||
- Bypass files entirely with `grim - | <inject to AI>`
|
||
- Clipboard-based workflow (`grim - | wl-copy`)
|
||
- Region capture with niri window geometry
|
||
- Real-time screen analysis
|
||
|
||
See `FUTURE-ENHANCEMENT.md` for details on direct capture.
|
||
|
||
## Deliverables
|
||
|
||
### Specification Documents (635 lines - ARCHIVED)
|
||
- ❌ `specs/001-screenshot-analysis/spec.md` - Over-specified
|
||
- ❌ `specs/001-screenshot-analysis/plan.md` - Premature planning
|
||
- ❌ `specs/001-screenshot-analysis/tasks.md` - 82 unnecessary tasks
|
||
|
||
### Implementation (185 lines - SHIPPED)
|
||
- ✅ `skills/screenshot-latest/SKILL.md` - Agent instructions
|
||
- ✅ `skills/screenshot-latest/scripts/find-latest.sh` - Working script
|
||
- ✅ `skills/screenshot-latest/README.md` - User docs
|
||
- ✅ `skills/screenshot-latest/examples/example-output.txt` - Example
|
||
|
||
### Analysis Documents (VALUABLE)
|
||
- ✅ `specs/001-screenshot-analysis/RESET.md` - Problem analysis
|
||
- ✅ `specs/001-screenshot-analysis/COMPARISON.md` - Spec vs reality
|
||
- ✅ `specs/001-screenshot-analysis/FUTURE-ENHANCEMENT.md` - Direct capture research
|
||
- ✅ `specs/001-screenshot-analysis/RESOLUTION.md` - This document
|
||
|
||
## Testing
|
||
|
||
**Manual test**:
|
||
```bash
|
||
./skills/screenshot-latest/scripts/find-latest.sh
|
||
# Expected: /home/dan/Pictures/Screenshots/Screenshot from 2025-11-08 14-06-33.png
|
||
# Actual: /home/dan/Pictures/Screenshots/Screenshot from 2025-11-08 14-06-33.png
|
||
✓ PASS
|
||
```
|
||
|
||
**Integration test**: Deploy to `~/.claude/skills/` and ask "look at my screenshot"
|
||
- Status: NOT YET TESTED (requires deployment)
|
||
- Next step: Deploy and validate with actual AI usage
|
||
|
||
## Deployment
|
||
|
||
### Not Yet Deployed
|
||
|
||
The skill needs to be deployed to:
|
||
- `~/.claude/skills/screenshot-latest` (for Claude Code), OR
|
||
- `~/.config/opencode/skills/screenshot-latest` (for OpenCode)
|
||
|
||
**Deployment command**:
|
||
```bash
|
||
# Claude Code
|
||
ln -s $(pwd)/skills/screenshot-latest ~/.claude/skills/screenshot-latest
|
||
|
||
# OpenCode
|
||
ln -s $(pwd)/skills/screenshot-latest ~/.config/opencode/skills/screenshot-latest
|
||
```
|
||
|
||
**Deployment blocked by**: Need to test in actual AI environment first
|
||
|
||
## Success Criteria
|
||
|
||
**Original (overcomplicated)**:
|
||
- SC-001: Work in 100% of cases (unmeasurable)
|
||
- SC-002: Complete in <1 second for 1000 files (premature optimization)
|
||
- SC-003: Succeed in 95% of requests (can't measure without data)
|
||
- SC-004: Clear error messages ✓ (kept this)
|
||
- SC-005: Save 40+ keystrokes ✓ (accurate)
|
||
|
||
**Actual (pragmatic)**:
|
||
1. User says: "look at my screenshot"
|
||
2. AI responds with analysis of correct file
|
||
3. User says: "thanks" (not "that's the wrong file")
|
||
|
||
**That's the only metric that matters.**
|
||
|
||
## Lessons for Future Features
|
||
|
||
### Specification Process
|
||
**Use comprehensive specs when**:
|
||
- Multiple developers need coordination
|
||
- Complex domain requiring analysis
|
||
- High risk of rework
|
||
- Unclear requirements needing clarification
|
||
- Enterprise/compliance requirements
|
||
|
||
**DON'T use comprehensive specs when**:
|
||
- Solution is obvious (1-liner test confirms)
|
||
- Single developer working alone
|
||
- Simple domain (file operations)
|
||
- Low risk of rework (<50 lines of code)
|
||
- Requirements are crystal clear
|
||
|
||
### Development Process
|
||
**For small features**:
|
||
1. Test one-liner solution (5 seconds)
|
||
2. If it works → Write script + docs (20 minutes)
|
||
3. Ship it
|
||
4. Iterate on feedback
|
||
|
||
**For large features**:
|
||
1. Write specification
|
||
2. Break down tasks
|
||
3. Implement incrementally
|
||
4. Test thoroughly
|
||
5. Ship after validation
|
||
|
||
**This feature was small. We should have skipped steps 1-2.**
|
||
|
||
## Related Work
|
||
|
||
**Research discoveries**:
|
||
- `grim -` can output PNG to stdout (verified)
|
||
- `niri msg` provides window geometry (verified)
|
||
- Direct capture approach is feasible (untested with AI)
|
||
- Clipboard injection is possible (untested with AI)
|
||
|
||
**Follow-up questions**:
|
||
- Can OpenCode/Claude Code read from clipboard?
|
||
- Can OpenCode/Claude Code accept base64 image data?
|
||
- What's the actual latency in real usage?
|
||
|
||
## Recommendations
|
||
|
||
### For This Feature
|
||
1. ✅ Ship current file-based implementation
|
||
2. ⏸️ Deploy to `~/.claude/skills/` or `~/.config/opencode/skills/`
|
||
3. ⏸️ Test with actual AI usage
|
||
4. ⏸️ Gather user feedback
|
||
5. ⏸️ Consider direct capture IF users request it
|
||
|
||
### For Future Features
|
||
1. Test before you specify
|
||
2. Build before you plan (for simple problems)
|
||
3. Question every requirement
|
||
4. Ship minimal version first
|
||
5. Enhance based on actual usage
|
||
|
||
### For Spec-Kit Tool
|
||
Consider adding a "complexity gate":
|
||
```
|
||
Before running /speckit.specify:
|
||
- Can you solve this with a one-liner?
|
||
- YES → Just write the code
|
||
- NO → Continue with specification
|
||
```
|
||
|
||
This would have saved 93 minutes on this feature.
|
||
|
||
## Status Summary
|
||
|
||
| Aspect | Status |
|
||
|--------|--------|
|
||
| Problem Understanding | ✅ Clear |
|
||
| Solution Validation | ✅ Tested (one-liner works) |
|
||
| Implementation | ✅ Complete (minimal version) |
|
||
| Documentation | ✅ Complete (SKILL.md + README) |
|
||
| Testing | ⚠️ Manual test passed, integration test pending |
|
||
| Deployment | ⏸️ Not yet deployed |
|
||
| User Validation | ⏸️ Awaiting real usage |
|
||
|
||
## Closure
|
||
|
||
**Original request**: "Make it so I don't have to type '~/Pictures/Screenshots' every time"
|
||
|
||
**Solution delivered**: 22-line bash script that finds latest screenshot automatically
|
||
|
||
**Time to implement**: 22 minutes
|
||
**Time to specify**: 115 minutes (wasted)
|
||
**Time to analyze**: 60 minutes (valuable - generated learning)
|
||
|
||
**Next action**: Deploy and test with actual AI usage
|
||
|
||
**Feature status**: ✅ RESOLVED (minimal viable implementation shipped)
|
||
|
||
---
|
||
|
||
*Sometimes the best specification is shipping working code.*
|