specflow-use

Connect Rosetta locally with Grid Dynamics SpecFlow MCP. Trigger only when the user mentions SpecFlow or SpecFlow workspaces and if SpecFlow MCP is already installed.

8 stars

Best use case

specflow-use is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Connect Rosetta locally with Grid Dynamics SpecFlow MCP. Trigger only when the user mentions SpecFlow or SpecFlow workspaces and if SpecFlow MCP is already installed.

Teams using specflow-use 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/specflow-use/SKILL.md --create-dirs "https://raw.githubusercontent.com/griddynamics/rosetta/main/instructions/r2/core/skills/specflow-use/SKILL.md"

Manual Installation

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

How specflow-use Compares

Feature / Agentspecflow-useStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Connect Rosetta locally with Grid Dynamics SpecFlow MCP. Trigger only when the user mentions SpecFlow or SpecFlow workspaces and if SpecFlow MCP is already installed.

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

# SpecFlow Use

This skill helps you drive **Grid Dynamics SpecFlow** from a local workspace via **SpecFlow MCP**. Rosetta stays local; SpecFlow runs everything remotely. The skill loads project context from `gain.json` and guides the user through SpecFlow MCP tool usage.

SpecFlow MCP is the only user interface to SpecFlow: you order work and download outputs. You do not connect to or operate on the remote workspaces directly.

## Quick Start

When the user mentions SpecFlow or works in a SpecFlow-enabled project:

1. **Detect** `gain.json` at the workspace root (and up to 2 parents). If missing, SpecFlow MCP will create it on the first tool call (together with `specflow_session.json`).
2. **Load** and summarize the project context.
3. **Guide** the user to the right phase using `references/specflow-mcp-tools.md`.

## Step 1: Detect gain.json

Check for `gain.json` at the current workspace root. If not found, check parent directories up to 2 levels. If still missing, tell the user this workspace is not yet initialized for SpecFlow — the first SpecFlow MCP tool call will create both `gain.json` and `specflow_session.json`.

## Step 2: Parse and Display Context

When `gain.json` is found, present a compact summary:

```
## SpecFlow Project Context

**Description**: [gain.json.description]
**Services**: specflow — [gain.json.servicesDescription.specflow]
             rosetta  — [gain.json.servicesDescription.rosetta]
**Supported Coding Agents**: [gain.json.codingAgents]
**Versions**:
  - rosetta: [gain.json.versions.rosetta]
  - specflow:    [gain.json.versions.specflow]
**Vocabulary overrides** (if present in gain.json.vocabulary):
  - (See references/specflow-vocabulary.md for defaults.)
```

### Version Compatibility Check

Compare `gain.json.versions.rosetta` with the current Rosetta version:

- **Minor difference**: warn and continue.
- **Major difference**: alert the user about potential incompatibilities.

## Step 3: Guide the User Journey

Read `references/specflow-mcp-tools.md` to route the user to the correct phase (pregeneration, generation, or post-run).

## Step 4: Consolidate Review Feedback

When SpecFlow returns a review report and the user wants to fix their specs before another iteration, delegate to Rosetta core:

- Skill: `skills/requirements-authoring`
- Workflow: `workflows/requirements-authoring-flow.md`

That skill handles iterative requirement updates with explicit user approval — matching the "consolidate the review report into updated specs" loop.

## Reference Files

Read as needed:

- `references/specflow-mcp-tools.md` — Phase routing and post-run skill bootstrap.
- `references/specflow-vocabulary.md` — Status values and checkpoint gates users encounter in responses.
- `references/specflow-schema.md` — Session files, version channels, and status enum quick lookup.

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