SKILL_TEMPLATE
[1-2 sentence description of what this skill does]. Triggers on [specific phrases/contexts that should activate this skill]. Outputs [what the skill produces].
Validates and registers new SoT IDs with cross-reference integrity. Triggers when creating BR-XXX, UJ-XXX, API-XXX, or CFD-XXX entries. Outputs formatted SoT entry with validated cross-references.
$ npx -y skills add mattgierhart/PRD-driven-context-engineering --skill ghm-id-register --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/ghm-id-registerContext preview
The summary Claude sees to decide when to auto-load this skill.
Validates and registers new SoT IDs with cross-reference integrity. Triggers when creating BR-XXX, UJ-XXX, API-XXX, or CFD-XXX entries. Outputs formatted SoT entry with validated cross-references.
name: ghm-id-register description: > Validates and registers new SoT IDs with cross-reference integrity. Triggers when creating BR-XXX, UJ-XXX, API-XXX, or CFD-XXX entries. Outputs formatted SoT entry with validated cross-references. context: fork allowed-tools: - Read - Write - Edit - Grep
Validate and register new Source of Truth IDs with cross-reference integrity checks.
1. **Validate Format** → Check ID follows `[PREFIX]-[3-digit]` pattern 2. **Check Uniqueness** → Ensure ID doesn't already exist 3. **Verify Cross-Refs** → All referenced IDs must exist 4. **Register Entry** → Add to appropriate SoT file
| Element | Definition | Evidence | |---------|------------|----------| | **ID** | Unique identifier | `BR-101`, `UJ-045`, `API-012` | | **Title** | Short descriptive name | Clear, specific | | **Cross-References** | Links to related IDs | All referenced IDs exist | | **Status** | Current state | Draft / Active / Deprecated |
| Prefix | Domain | File | |--------|--------|------| | `BR-` | Business Rules | `SoT/SoT.BUSINESS_RULES.md` | | `UJ-` | User Journeys | `SoT/SoT.USER_JOURNEYS.md` | | `API-` | API Contracts | `SoT/SoT.API_CONTRACTS.md` | | `CFD-` | Customer Feedback | `SoT/SoT.customer_feedback.md` |
Check ID follows the pattern:
[PREFIX]-[XXX]
Where:
1. Read target SoT file 2. Extract all existing IDs of same prefix 3. Verify new ID doesn't exist 4. If auto-assigning: use highest existing + 1
For each ID referenced in the new entry: 1. Identify the prefix 2. Check that ID exists in its SoT file 3. Flag any missing references
Before registering, assign a confidence score (1-5) based on evidence strength:
| Score | Evidence Level | Examples | |-------|----------------|----------| | 1/5 | Assumption / PM decision | "We think users want X" | | 2/5 | Secondary research | Competitive analysis, market report | | 3/5 | Direct feedback | User interviews (3-5 conversations) | | 4/5 | Validated behavior | Beta testing, small-scale usage | | 5/5 | Production evidence | Real usage data at scale |
**Question to ask**: What's the highest evidence supporting this entry right now? What would move it to the next confidence level?
**Example confidence annotations**:
See `.claude/skills/PRINCIPLES.md` for detailed confidence model by SoT type.
Add formatted entry to SoT file:
### [ID]: [Title] **Status**: Draft **Created**: YYYY-MM-DD **Confidence**: [1-5]/5 (source: [evidence source]) **Next Confidence Target**: [What would move this to next level] **Cross-References**: [List of related IDs] [Description] **Acceptance Criteria**: - [ ] Criterion 1 - [ ] Criterion 2
**Example entry with confidence**:
### CFD-042: Users want dark mode **Status**: Active **Created**: 2026-02-01 **Confidence**: 3/5 (source: 5-user-interviews-jan-2026) **Next Confidence Target**: 4/5 (would require beta cohort validation) **Cross-References**: FEA-008 (dark mode feature) During interviews, 4 of 5 users mentioned desire for dark mode. Competitors (Notion, Linear, Figma) all have it. **Acceptance Criteria**: - [ ] Feature FEA-008 delivered to beta cohort - [ ] Track usage: % of beta users enabling dark mode
| Pattern | Example | Fix | |---------|---------|-----| | Duplicate ID | Creating BR-101 when it exists | → Check uniqueness first | | Orphan reference | References UJ-999 that doesn't exist | → Verify all cross-refs | | Wrong prefix | Using BR- for an API contract | → Match prefix to domain | | Missing zero-pad | BR-5 instead of BR-005 | → Always use 3 digits | | Inflated confidence | Assigning 4/5 to a PM assumption | → Be honest about evidence level | | No confidence source | "confidence: 3/5" with no source | → Always record source (CFD-001, user-interview-jan, etc.) | | Missing confidence target | Confidence assigned but no forward path | → Ask "what would move this to 4/5?" |
**DO**:
**DON'T**:
After ID registration:
PRD-Led Context Engineering — Memory as Infrastructure. An ontology layer for product teams building products that solve real problems — with AI agents that remember. Gated PRD, typed IDs, markdown knowledge graph, Claude Code skills & hooks.
Repo: mattgierhart/PRD-driven-context-engineering
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