do-write-scenarios

A set of rules for writing behavior-driven development feature files. BDD feature files describe what a user should be able to do through concrete scenarios before implementation begins.

In plain words
What is it for?
Use it to create feature specifications and scenarios for application behavior, including who performs an action, why they do it, and what should happen.
Why use it?
Vague scenarios make requirements and tests difficult to understand. These rules encourage clear users, goals, reasons, conditions, and expected behavior.

Cursor rule for Cursor

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add rules/featurefactory-io/mimir/do-write-scenarios
Clone the repo
git clone --depth 1 https://github.com/FeatureFactory-io/mimir

Made for: Cursor.

Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 915 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00915
Opus 5 $0.00000 $0.00458
Sonnet 5 $0.00000 $0.00183
Haiku 4.5 $0.00000 $0.00092

Measured 2d ago against content hash 98c4b9fd03d2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

do-write-scenarios scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/rules/do-write-scenarios.mdc · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Writing Effective BDD Feature Files

1. Principle: Always Start With a Feature Specification

  • Before writing any feature story, check if a feature specification exists.
  • If it does not exist, write one first. A good feature spec:
    • Assess docs/ux/demo-flow.md - what we are doing and why? what will be affected?
    • Defines the user (role or persona).
    • States the goal (what the user wants to achieve).
    • Describes the context (why the goal matters).
    • Clarifies any assumptions or preconditions.
    • Consist of one or many scenarios user is going through to achieve the goal
    • Pick an ID (like a prefix for all scenarios in the file), like abbreviation "Library" -> LIB, "Dataset" - DS etc.
    • Analyze the codebase - which pages/views are already available? what we will use? what we will build?

Example Feature Spec

Alex Chen wants to apply a moving average to Apple stock price data so they can observe trends and test signals over a historical period.


2. Principle: Be Specific — Who Does What, and Why

Each Scenario should:

  • Identify the actor clearly (Fund Analyst, Quant, User).
  • Describe what they are trying to do, in plain English, very specific - "Enters ABC into XYZ"
  • State why it matters for the workflow or outcome.
  • Capture precise values — asset identifiers, transformations, expected results.
  • Have ID like "Scenario: LIB 1.1 Add Dataset"

3. Structure

Each Scenario should follow the format:

Scenario: <ID> <User goal>
  Given <initial system state or data>
  When <action is taken>
  Then <expected result or outcome>

Include exact DSL inputs, parameter values, and visual/verbal feedback expectations.


4. Example: Data Transformation Scenario

Feature: DSL 1.1 Applying SMA transformation to a selected equity

  Scenario: Applies applies 12-month simple moving average to AAPL equity
    Given the user is in the "Workspace"
    And the asset "US.Equity.AAPL" is selected in the data table "Assets"
    When the user applies "transformation" "SMA(12)" to the time series in the row
    Then the chart "Moving Avg: should update to show a new line representing the 12-month SMA
    And the data table "Moving Avg: Table" should display the transformed values under a new column

Read the full file on GitHub · 108 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 108 lines · 0 tokens per session scan A 98c4b9fd03d2

Subscribe to this mod's changes

do-write-scenarios is a cursor rule published in the GitHub repository FeatureFactory-io/mimir (13 stars, last pushed 4d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 915 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.