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Use when analyzing work history to identify major projects and group related PRs and tickets together.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | work-chronicler-detect-projects |
| description | Use when analyzing work history to identify major projects and group related PRs and tickets together. |
| user-invocable | true |
| disable-model-invocation | true |
Analyze work history to identify major projects and group related work.
Active profile: !work-chronicler workspace profile
Work log: !work-chronicler workspace work-log
Analysis: !work-chronicler workspace analysis
For non-Claude tools: Run
work-chronicler workspace work-logto get your data path.
Note: Project detection is now built into the CLI. Run work-chronicler analyze --projects to generate projects.json. This skill is for reviewing and refining those results.
<work-log>/
├── filtered/ # ⭐ USE THIS IF IT EXISTS (pre-filtered subset)
│ ├── .analysis/
│ ├── pull-requests/
│ └── jira/
├── .analysis/
│ ├── projects.json # Pre-computed project groupings (use this first!)
│ ├── stats.json # Impact breakdown, repo stats
│ └── timeline.json # Chronological view
├── pull-requests/
│ └── <org>/<repo>/*.md
└── jira/
└── <org>/<project>/*.md
Start with projects.json (if it exists):
Review and refine groupings:
For manual detection (if projects.json doesn't exist):
IMPORTANT: You must do BOTH of the following:
<profile-root>/outputs/projects-detected-YYYY-MM-DD.mdGet the profile root with: work-chronicler workspace root
This ensures users have both immediate feedback AND a persistent file they can reference later.
For each project, gather:
## Detected Projects
### 1. Authentication Overhaul (High Confidence)
**Period**: January - March 2025
**Scope**: 5 PRs, 4 tickets, +5,200 / -1,800 lines
**Impact**: 3 flagship, 2 major
**Tickets**:
- DWP-575: Add cursor command for creating jira ticket
- DWP-576: Create honeycomb-env package
- DWP-577: Refactor helm charts
- DWP-578: Update deployment scripts
**Key Deliverables**:
- OAuth2 integration with multiple providers
- TOTP-based MFA support
- Secure session handling with refresh tokens
---
### 2. Performance Optimization (High Confidence)
**Period**: April - June 2025
**Scope**: 8 PRs, 3 tickets, +3,100 / -900 lines
**Impact**: 2 flagship, 4 major, 2 standard
**Tickets**:
- DWP-463: Eater app lambda optimization
- DWP-529: Caching layer implementation
- DWP-530: Database query optimization
**Key Deliverables**:
- 73% reduction in API latency
- 60% reduction in database load
---
### 3. Unrelated Work Cluster (Low Confidence - Needs Review)
**Period**: July 2025
**Scope**: 12 PRs, 0 tickets, +800 / -200 lines
*This cluster was detected by time proximity. Review PRs to determine if they form a cohesive project or should be split.*
PRs: #4074, #4091, #4094, #4096, #4098, #4103, #4104, #4109, #4110, #4114, #4120, #4126
Use when identifying recurring themes in work history for career narrative and skill development tracking.
Use when creating achievement-focused resume bullet points from work history. Extracts impactful accomplishments for resumes.
Use when preparing for performance reviews, 1:1s, or summarizing accomplishments. Reads PRs and tickets from work-chronicler workspace.
Use when updating an existing resume with recent accomplishments from work history. Matches existing resume format and tone.
Use when drafting self-review content for performance reviews. Analyzes work history to create structured review narratives.
Write peer reviews for colleagues. Use when writing peer feedback, 360 reviews, or colleague evaluations. Supports both evidence-based reviews (with work-log data) and narrative reviews (notes-only).