# Model Usage Map

## 1. Purpose

This file tracks where models are used.

It answers:

```text
Which Agents use this model?
Which Skills execute this model?
Which Runtimes orchestrate this model?
Which Prompt Cards embed this model?
Which Model Cards are unused?
Which models have many dependents and require careful versioning?
```

Usage mapping makes model maintenance possible.

If a model changes, this file helps identify what else should be reviewed.

## 2. Usage Categories

Track usage across:

```text
Agents
Prompt Cards
Skills
Runtimes
Committees
Reports
Templates
Knowledge Workflows
```

## 3. Mapping Format

Use this format:

```md
## {model-id}

### Model Name

### Status

### Prompt Cards

### Agents

### Skills

### Runtimes

### Committees

### Knowledge Workflows

### Notes
```

## 4. Initial Usage Map

## cognitive-imaging

### Model Name

认知显影术 / Cognitive Imaging

### Status

```text
draft
```

### Prompt Cards

Potential:

```text
agents/lite/cognitive-imaging-specialist.prompt.md
```

### Agents

Potential:

```text
agents/agent-specs/cognitive-imaging-specialist.agent.md
```

### Skills

Potential:

```text
skills/cognitive/cognitive-imaging.skill.md
skills/cognitive/prediction-error-capture.skill.md
skills/cognitive/do-operator-test.skill.md
```

### Runtimes

Potential:

```text
runtimes/hybrid/review-committee.runtime.md
runtimes/interactive/modeling-committee.runtime.md
```

### Committees

Potential:

```text
Review Committee
Modeling Committee
```

### Knowledge Workflows

Potential:

```text
article-review-workflow
model-mining-workflow
```

### Notes

Currently known as a self-contained model embedded in the Cognitive Imaging Specialist Agent.

Recommended future structure:

```text
Model Card
+ Cognitive Skill
+ Agent Spec
+ optional Lite Prompt
+ optional Review Committee Runtime node
```

## giant-cognition

### Model Name

巨人认知 / Giant Cognition

### Status

```text
candidate
```

### Prompt Cards

```text
TBD
```

### Agents

```text
TBD
```

### Skills

```text
TBD
```

### Runtimes

```text
TBD
```

### Committees

Potential:

```text
Review Committee
```

### Knowledge Workflows

```text
TBD
```

### Notes

Requires source review and Model Mining.

## cognitive-prism

### Model Name

认知棱镜 / Cognitive Prism

### Status

```text
candidate
```

### Prompt Cards

```text
TBD
```

### Agents

```text
TBD
```

### Skills

```text
TBD
```

### Runtimes

```text
TBD
```

### Committees

Potential:

```text
Review Committee
```

### Knowledge Workflows

```text
TBD
```

### Notes

Requires source review and Model Mining.

## 5. Usage Review Checklist

When adding usage, check:

```text
Is this model actually used, or merely related?
Is it embedded directly in a Prompt Card?
Is it referenced by an Agent Spec?
Is it executed by a Skill?
Is it orchestrated by a Runtime?
Is the usage active, candidate, or planned?
```

## 6. Maintenance Rules

When a Model Card changes:

```text
1. Check related Prompt Cards.
2. Check related Agent Specs.
3. Check related Skills.
4. Check related Runtimes.
5. Update usage notes.
6. Mark affected artifacts for review if needed.
```

## 7. High-Impact Model Rule

If many artifacts depend on a model, mark it as high-impact.

High-impact models require:

```text
Careful versioning
User approval before major changes
Migration notes
Affected artifact review
```

## 8. Unused Model Rule

If a model has no usage, decide whether it is:

```text
A theoretical asset
A future candidate
A deprecated model
An extraction artifact
A model awaiting Skill or Agent conversion
```

Do not delete unused models automatically.

## 9. Final Rule

A model library becomes powerful when models are not only stored, but connected.

Usage mapping turns isolated ideas into operational cognitive infrastructure.