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Ghm Id Register

Community
mattgierhart
ghm-id-register

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.

Overview

Publishermattgierhart
RepositoryPRD-driven-context-engineering
Skill nameghm-id-register
Stars
179
Forks
11
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mattgierhart on GitHub. Read the source before you install it.

Installation

Install the Ghm Id Register AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mattgierhart/PRD-driven-context-engineering.git /tmp/PRD-driven-context-engineering
mkdir -p .claude/skills
cp -r /tmp/PRD-driven-context-engineering/plugins/prd-ce/skills/ghm-id-register .claude/skills/ghm-id-register
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ghm Id Register in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ghm Id Register on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ghm Id Register is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ID Register

Validate and register new Source of Truth IDs with cross-reference integrity checks.

Workflow Overview

  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

Core Output Template

ElementDefinitionEvidence
IDUnique identifierBR-101, UJ-045, API-012
TitleShort descriptive nameClear, specific
Cross-ReferencesLinks to related IDsAll referenced IDs exist
StatusCurrent stateDraft / Active / Deprecated

ID Format Reference

PrefixDomainFile
BR-Business RulesSoT/SoT.BUSINESS_RULES.md
UJ-User JourneysSoT/SoT.USER_JOURNEYS.md
API-API ContractsSoT/SoT.API_CONTRACTS.md
CFD-Customer FeedbackSoT/SoT.customer_feedback.md

Step 1: Validate Format

Check ID follows the pattern:

[PREFIX]-[XXX]

Where:

  • PREFIX = BR, UJ, API, or CFD
  • XXX = 3-digit number (zero-padded)

Checklist

  • Prefix is valid (BR, UJ, API, CFD)
  • Number is 3 digits
  • Format matches [A-Z]+-[0-9]{3}

Step 2: Check Uniqueness

  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

Checklist

  • Target SoT file read
  • Existing IDs enumerated
  • New ID is unique

Step 3: Verify Cross-References

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

Checklist

  • All BR-XXX references exist in BUSINESS_RULES
  • All UJ-XXX references exist in USER_JOURNEYS
  • All API-XXX references exist in API_CONTRACTS
  • All CFD-XXX references exist in CUSTOMER_FEEDBACK
  • Each cross-reference includes a relationship type (see references/cross-reference-patterns.md)
  • Relationship types match the directional hierarchy (vertical types for cross-layer, lateral types for same-layer)

Step 3.5: Evaluate Confidence (NEW)

Before registering, assign a confidence score (1-5) based on evidence strength:

ScoreEvidence LevelExamples
1/5Assumption / PM decision"We think users want X"
2/5Secondary researchCompetitive analysis, market report
3/5Direct feedbackUser interviews (3-5 conversations)
4/5Validated behaviorBeta testing, small-scale usage
5/5Production evidenceReal 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:

  • confidence: 2/5, source: competitive-analysis
  • confidence: 3/5, source: 5-user-interviews-jan-2026
  • confidence: 4/5, source: beta-cohort-validation

See .claude/skills/PRINCIPLES.md for detailed confidence model by SoT type.

Checklist

  • Confidence score assigned (1-5)
  • Highest evidence source identified
  • Forward path identified ("would move to X/5 if...")

Step 4: Register Entry

Add formatted entry to SoT file:

markdown
### [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:

markdown
### 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

Quality Gates

Pass Checklist

  • ID format is valid
  • ID is unique within its domain
  • All cross-references resolve
  • Entry follows SoT template
  • Confidence score assigned (1-5) with source documented
  • Next confidence target identified

Testability Check

  • ID can be searched and found
  • Cross-references are bidirectional (if required)
  • Confidence score is honest (reflects actual evidence, not wishful thinking)

Anti-Patterns

PatternExampleFix
Duplicate IDCreating BR-101 when it exists→ Check uniqueness first
Orphan referenceReferences UJ-999 that doesn't exist→ Verify all cross-refs
Wrong prefixUsing BR- for an API contract→ Match prefix to domain
Missing zero-padBR-5 instead of BR-005→ Always use 3 digits
Inflated confidenceAssigning 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 targetConfidence assigned but no forward path→ Ask "what would move this to 4/5?"

Boundaries

DO:

  • Format validation
  • Uniqueness checks
  • Cross-reference verification
  • Entry formatting

DON'T:

  • Content decisions about ID meaning
  • Approve/reject based on business logic
  • Modify existing IDs

Handoff

After ID registration:

  • New ID is in SoT file
  • Cross-references are valid
  • EPIC Execution Plan updated with new ID
  • Ready for implementation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ghm Id Register AI skill do?

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.

Why use Ghm Id Register on TypingMind?

Because you install it once and use it with any model. Ghm Id Register is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ghm Id Register in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mattgierhart/PRD-driven-context-engineering/tree/main/plugins/prd-ce/skills/ghm-id-register. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ghm Id Register?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ghm Id Register?

As many as you like. As long as a model supports skills, you can use Ghm Id Register with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ghm Id Register AI skill free?

Yes. It is published on GitHub by mattgierhart under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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