ankn
a5f8fb49ab
Bahn: aisupport, Analyse-O2C-C2S, awesome-bahn-mcp-servers, beam-mcp,
Confluence_Bot, db-planet-mcp-server, O2C-Harness, project-audit,
Projekt-KIQ-HP, teamlandkarte-mcp
Dhive: Jury-Voting
Privat: CV, NoteGraph (NOTE: NoteGraph needs complete redo after consolidation)
Shared: AI-Orchestrator, OrgMyLife, power_skills_and_more
Shared/references: symphony (read-only)
Bahn repos remain available as independent remotes - this monorepo
pulls them in via subtree, the originals are untouched.
113 lines
4.8 KiB
Markdown
113 lines
4.8 KiB
Markdown
# SPEC.md — Personal Knowledge Base
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## Purpose
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A file-based personal knowledge graph that stores structured professional information in YAML, enabling tailored CV generation, interview-based knowledge collection, speaker introductions, and iterative review workflows. The file system is the database — no build step, no server, no compilation required.
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## Tech Stack
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| Layer | Technology |
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|-------|-----------|
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| Data format | YAML (one file per entity) |
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| Validation & logic | TypeScript (strict mode) |
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| Testing | Vitest + fast-check (property-based) |
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| Runtime | Node.js (v24+) |
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| Version control | Git |
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| Automation | Kiro skills (.kiro/skills/) |
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## Architecture
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```
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project-root/
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├── kb/ # Knowledge base data (YAML entities)
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│ ├── profiles/ # Person profiles
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│ ├── experiences/ # Work experiences
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│ ├── skills/ # Skills
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│ ├── organizations/ # Organizations
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│ ├── projects/ # Projects
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│ ├── certifications/ # Certifications
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│ ├── tandems/ # Job sharing tandems
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│ └── graph-index.yaml # Central entity/relationship index
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├── templates/ # Document generation templates
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├── output/ # Generated documents (CVs, intros)
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├── sources/ # Imported source documents
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├── src/ # TypeScript validation and logic
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│ ├── schemas/ # Entity interfaces and validation
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│ ├── io/ # YAML serialization and file I/O
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│ ├── graph/ # Graph index management
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│ ├── interview/ # Gap and conflict detection
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│ ├── cv/ # Relevance selection and tandem generation
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│ ├── intro/ # Introduction generation
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│ └── review/ # Completeness scoring and prioritization
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└── .kiro/skills/ # Kiro agent skills
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├── interview-collect/ # Knowledge collection via interview
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├── cv-generate/ # Tailored CV generation
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├── talk-intro/ # Speaker introduction generation
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└── kb-review/ # Knowledge base review
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```
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## Entity Types
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- **Person** — name, contact, summary, education, languages, references to skills/experiences/certifications
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- **Experience** — title, organization, dates, description, achievements, skills-used
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- **Skill** — name, category, level, years, context
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- **Organization** — name, industry, optional parent
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- **Project** — name, description, organization, dates, skills-used, persons
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- **Certification** — name, issuer, date, expires, person
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- **Tandem** — exactly 2 partners, shared-vision, complementary-skills, collaboration-model
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## Relationship Types
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`has_skill`, `worked_at`, `collaborated_with`, `applied_for`, `partners_with`
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## Kiro Skills
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| Skill | Purpose |
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|-------|---------|
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| interview-collect | Focused interview sessions (max 10 questions) to collect/update KB data |
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| cv-generate | Tailored CVs matched against job postings; supports tandem applications |
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| talk-intro | Speaker introductions in 3 length variants adapted to event context |
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| kb-review | Completeness scoring, staleness detection, review prioritization |
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## Conventions
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- File naming: kebab-case (`<entity-id>.yaml`)
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- One file per entity
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- Graph index updated on every entity change
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- All data human-readable and diffable in Git
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- TypeScript interfaces use camelCase (deserialized form of kebab-case YAML)
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## Rules
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1. Never fabricate content in generated documents — only use data present in the knowledge base.
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2. Validate entities against schema before persisting.
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3. Enforce temporal consistency (start ≤ end) for time-bound entities.
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4. Create and use Kiro skills whenever a task of more than 5 lines of code runs for the second time.
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## Correctness Properties
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15 formal properties validated via property-based testing (fast-check):
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1. Entity serialization round-trip
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2. Entity schema validation
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3. Temporal consistency
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4. Graph index consistency
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5. Tandem entity integrity
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6. Interview session question limit (≤ 10)
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7. Gap detection completeness
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8. Conflict detection
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9. CV relevance selection ordering
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10. Tandem application document set (exactly 3 docs)
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11. CV output validity and traceability
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12. Introduction length variants (short < medium < long)
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13. Completeness score calculation
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14. Review prioritization ordering
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15. File naming convention (kebab-case)
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## Current State
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- Directory structure: created
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- TypeScript project: initialized, dependencies installed
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- Entity interfaces: defined (src/schemas/types.ts)
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- Validation, I/O, graph, skills, tests: pending implementation
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