ms-context

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ms-context — AI Agent Context Prompt Generation

Behavior

1. Reads mission.yaml and extracts goal, constraints, and completion criteria.
2. Includes design document locations from design_refs if available.
3. Extracts evolution summary and latest changes from mission-history.yaml.
4. Collects key decision titles from .mission/decisions/MDR-*.md.
5. Renders module structure as a table from .mission/architecture/ARCHITECTURE_CURRENT.yaml.
6. Extracts public API list from .mission/interfaces/API_REGISTRY.yaml.
7. Combines all information into a single markdown output.

How to Run

node -e "
import { generateContext } from '${CLAUDE_PLUGIN_ROOT}/dist/commands/context.js';
const c = generateContext('.');
console.log(c.markdown);
"

Output Format

# Project Context

## Mission: Mission Title

**Goal:** Mission goal
**Version:** 1.7.0

### Constraints

- Constraint 1

### Done When

- Completion criterion 1

## Design References

- **architecture:** `docs/internal/ARCHITECTURE.md`

## Evolution Summary

**Current Phase:** architecture-assetization — Architecture knowledge assetization
**Total Revisions:** 7

## Key Decisions (MDR)

- **MDR-001-task-contract-only.md:** MDR-001: Task Contract Only

## Architecture

| Module | Path                 | Responsibility        | Depends On |
| ------ | -------------------- | --------------------- | ---------- |
| parser | `src/core/parser.ts` | YAML parse + validate | validator  |

## Public API

- `generateContext(projectDir: string) => ContextResult`

Notes

• Returns an error if mission.yaml is missing.
• Each optional section (history, architecture, API, etc.) is automatically omitted if the corresponding file is missing.
• The output can be used as a system prompt or first message for a new AI agent.
• The sections array in the return value indicates which sections were included.