init-workspace-documentation

Rosetta skill to create CONTEXT.md, ARCHITECTURE.md, IMPLEMENTATION.md, ASSUMPTIONS.md, and AGENT MEMORY.md from workspace analysis.

8 stars

Best use case

init-workspace-documentation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Rosetta skill to create CONTEXT.md, ARCHITECTURE.md, IMPLEMENTATION.md, ASSUMPTIONS.md, and AGENT MEMORY.md from workspace analysis.

Teams using init-workspace-documentation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/init-workspace-documentation/SKILL.md --create-dirs "https://raw.githubusercontent.com/griddynamics/rosetta/main/instructions/r2/core/skills/init-workspace-documentation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/init-workspace-documentation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How init-workspace-documentation Compares

Feature / Agentinit-workspace-documentationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Rosetta skill to create CONTEXT.md, ARCHITECTURE.md, IMPLEMENTATION.md, ASSUMPTIONS.md, and AGENT MEMORY.md from workspace analysis.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

<init_workspace_documentation>

<role>
Senior technical writer — recovers intent from code, not transcribes implementation.
</role>

<when_to_use_skill>
Workspaces lack structured documentation, forcing every session to re-discover facts and repeat mistakes. This skill creates five foundational docs from source code analysis. Proof: all five docs exist, are non-empty, complementary, and track unknowns.
</when_to_use_skill>

<core_concepts>

- All Rosetta prep steps MUST be FULLY completed, load-context skill loaded and fully executed
- ACQUIRE `reverse-engineering/SKILL.md` FROM KB and EXECUTE for domain extraction
- Existing project documentation is likely stale and incomplete: source code is the true source of truth
- Documentation phase is based on discovery phase to perform **deep** analysis, but avoid reading entire codebase.
- Select which files to read, group organize by modules/batches/groups and must assign to subagents to execute.

</core_concepts>

<process>

1. Dual-mode based on state.mode:
   - Scan for each target doc file
   - Compare existing content against codebase findings
   - install = create all; upgrade = update gaps only
   - Never overwrite human-added content; merge alongside
   - Report created/updated/skipped files
2. Analyze project structure and key source files
3. Create TODO task per document with business context angle
4. Track unknowns in ASSUMPTIONS.md with forward references
5. Create or update documents:

CONTEXT.md:
- What this doc is for and what it should contain, self-defining style
- Self-defines purpose, content type, style
- Bulleted business context, purpose, domain — stakeholder perspective
- No technical details

ARCHITECTURE.md:
- What this doc is for and what it should contain, self-defining style
- Self-defines purpose, content type, style
- Architecture, modules, workspace structure, testing, styling, building blocks
- No business context — reference CONTEXT.md
- Reference CODEMAP.md for file structure

IMPLEMENTATION.md:
- What this doc is for and what it should contain, self-defining style
- Self-defines purpose, content type, style
- Baseline state VERY BRIEFLY (first part, use word "Baseline" in header, not word "current" - misleading later on)
- High-level change log, each change separate header with date and description (second part)
- DRY — reference other docs
- The only implementation change log
- If nothing to add - add template

ASSUMPTIONS.md:
- What this doc is for and what it should contain, self-defining style
- Self-defines purpose, content type, style
- Each entry: assumption, confidence level, target file when resolved
- Revalidate all assumptions after other documents complete
- If nothing to add - add template

TODO.md:
- What this doc is for and what it should contain, self-defining style
- Self-defines purpose, content type, style
- Each entry comes with header containing "priority when what where" and body with details
- If nothing to add - add template

AGENT MEMORY.md:
- What this doc is for and what it should contain, self-defining style
- Self-defines purpose, content type, style
- Must follow the template exactly - it will be updated during use
- Keep template entries so that AI knows how to fill them in later on
- It is for agent operational notes, not a duplicate of CONTEXT.md/ARCHITECTURE.md

README.md:
- Create in workspace and in each repository root README.md files if missing

6. Special cases:
   - Speckit: if `memory/constitution.md` and `specs` folder exist, add "MUST ACQUIRE speckit-integration-policy.md FROM KB and execute it" to CONTEXT.md
   - Composite (state.composite = true): create top-level docs as registries with workspace-relative paths to sub-repo docs
   - If large project add "MUST USE SKILL `large-workspace-handling`" to CONTEXT.md

</process>

<validation_checklist>
- Each document contains self-definition of purpose and style
- Documents complement without repeating each other
- ASSUMPTIONS.md entries have forward references to target documents
- Upgrade mode: human content preserved, only gaps filled
- Files can be grepped by headers for useful information and ToC
</validation_checklist>

<templates>

### AGENT MEMORY.md

```markdown
# AGENT MEMORY

Generalized reusable lessons from agent sessions.
Root causes converted into preventive rules, not incident-specific notes.
Entries are h3 headers with [ACTIVE|RETIRED] status.
Content: brief, grep-friendly, MECE across sections. 
Style: one-liner per entry, optional sub-bullets for context.
Keep template entries so that AI knows how to fill them in later on.

## Preventive Rules

### <Generalized Preventive Rule> [ACTIVE|RETIRED]
[Root cause, Reasons, Problems]

## What Worked

### <Generalized What Worked> [ACTIVE|RETIRED]
[Root cause, Reasons, Problems]

## What Failed

### <Generalized What Failed> [ACTIVE|RETIRED]
[Hypothesis, Root cause, Reasons, Problems]

## Discoveries

### <Generalized Discovery> [ACTIVE|RETIRED]
[Usage, Reasons, Problems]
```

</templates>

</init_workspace_documentation>

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