TalonT-Org

make-scenarios

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# Install this skill:
npx skills add TalonT-Org/AutoSkillit --skill "make-scenarios"

Install specific skill from multi-skill repository

# Description

Analyze a plan or codebase to generate scenarios in "Actor wants to..." format from a stated perspective. Use when user says "make scenarios", "generate scenarios", "jeopardy requirements", or wants to identify extension points and use cases.

# SKILL.md


name: make-scenarios
description: Analyze a plan or codebase to generate scenarios in "Actor wants to..." format from a stated perspective. Use when user says "make scenarios", "generate scenarios", "jeopardy requirements", or wants to identify extension points and use cases.
hooks:
PreToolUse:
- matcher: "*"
hooks:
- type: command
command: "echo '[SKILL: make-scenarios] Generating scenarios...'"
once: true


Scenario Generation Skill

Analyze a plan, codebase, or feature description and produce scenarios — statements of what an actor wants to be able to do. Scenarios are perspective-driven: the user provides the lens (developer extensibility, end-user capability, operator workflow, security posture, etc.) and the skill discovers what scenarios matter from that perspective.

Scenarios follow the form: "{Actor} wants to {action} {target}"

These scenarios become input for requirements generation via /make-req in a separate session.

When to Use

  • User says "make scenarios", "generate scenarios", "jeopardy requirements"
  • User wants to discover extension points, use cases, or capability gaps
  • User wants to understand what a system should accommodate from a specific perspective

Core Principles

  • Scenarios are perspective-dependent. The same codebase yields different scenarios for a developer vs. an end-user vs. an operator. The user provides the perspective.
  • Scenarios state desires, not solutions. Each scenario says what an actor wants to achieve, never how the system should enable it.
  • Scenarios are discovered, not invented. They emerge from what the codebase or plan reveals — variation points, hardcoded assumptions, existing abstractions, domain concepts.

Critical Constraints

NEVER:
- Modify any source code files
- Create files outside temp/make-scenarios/ directory
- Prescribe solutions or approaches in scenarios
- Invent scenarios that have no basis in the analyzed material
- Mix perspectives in a single scenario (each scenario has one actor type)

ALWAYS:
- Require the user to state the perspective/lens before proceeding
- Use subagents for parallel exploration
- Ground every scenario in evidence from the codebase or plan
- Write output to temp/make-scenarios/ directory

Workflow

Step 0: Establish Perspective

If the user has not stated a perspective, ask. Examples:

  • Developer extensibility: "Developer wants to add/swap/extend..."
  • End-user capability: "User wants to filter/export/customize..."
  • Operator workflow: "Operator wants to monitor/configure/rotate..."
  • Security posture: "Attacker wants to escalate/exfiltrate/bypass..."
  • Data analyst: "Analyst wants to query/export/visualize..."

The perspective determines what the subagents look for and how scenarios are framed.

Step 1: Analyze Source Material

Identify the input: a plan file, codebase area, feature description, or conversation context. Read it fully.

Launch parallel Explore subagents tailored to the stated perspective:

For developer extensibility perspective:
- Variation points — Where does the system parameterize behavior?
- Hardcoded assumptions — Where is the system locked to one implementation?
- Extension patterns — Base classes, registries, plugin directories, strategy patterns
- Domain entities — First-class concepts that could reasonably be added or swapped

For end-user capability perspective:
- User-facing behaviors — What can the user do today?
- Workflow gaps — Where does the user hit dead ends or workarounds?
- Configuration surface — What can/can't the user control?
- Output formats — What forms does data take when presented to users?

For operator workflow perspective:
- Deployment topology — How is the system run?
- Configuration mechanisms — What knobs exist?
- Observability — What can be monitored, what's opaque?
- Recovery paths — What happens on failure?

For security posture perspective:
- Trust boundaries — Where does the system validate input?
- Privilege levels — What access controls exist?
- Data exposure — What sensitive data flows where?
- Attack surface — What interfaces are externally reachable?

Adapt subagent prompts to the stated perspective. The above are examples, not exhaustive categories.

Step 2: Identify Scenario Candidates

From subagent findings, extract candidate scenarios. For each:

  1. Frame as "{Actor} wants to {action} {target}"
  2. Note the evidence — what in the codebase or plan revealed this scenario
  3. Note the current state — does the system support this partially, not at all, or fully?

Discard scenarios where the system already fully supports the capability (nothing to require).

Step 3: Curate and Rank

  • Remove duplicates and overlapping scenarios
  • Rank by significance: scenarios that would require the most architectural consideration come first
  • Aim for 5-15 scenarios. Fewer if the scope is narrow, more if analyzing a broad system
  • Group related scenarios under thematic headings if natural groupings emerge

Step 4: Write the Scenarios Document

Save to: temp/make-scenarios/scenarios_{perspective}_{topic}_{YYYY-MM-DD_HHMMSS}.md

# Scenarios: {Topic}

**Date:** {YYYY-MM-DD}
**Source:** {What was analyzed — plan name, codebase area, or description}
**Perspective:** {The stated perspective/lens}

## Overview
{One paragraph: what these scenarios describe, the perspective used, and their intended use as input for requirements generation}

---

## {Thematic Group 1} (if grouping applies)

### SCEN-001: {Actor} wants to {action} {target}
**Evidence:** {What in the codebase/plan revealed this}
**Current state:** {Not supported | Partially supported | Hardcoded to single implementation}

### SCEN-002: {Actor} wants to {action} {target}
**Evidence:** {…}
**Current state:** {…}

---

## {Thematic Group 2}

### SCEN-003: {Actor} wants to {action} {target}
**Evidence:** {…}
**Current state:** {…}

---

{Repeat for each scenario}

Numbering: Sequential across the entire document (SCEN-001 through SCEN-NNN).

Step 5: Provide Follow-Up Instructions

After writing the file, output to terminal:

Scenarios written to: temp/make-scenarios/scenarios_{perspective}_{topic}_{timestamp}.md

Review and edit the scenarios file — remove any you don't want requirements for.
Then in a new session, run /make-req with the scenarios file as input.

Output Quality Checks

Before finalizing, verify:

  • Every scenario names a specific actor and a specific desire
  • Every scenario has evidence grounded in the analyzed material
  • No scenario prescribes a solution or technology
  • Scenarios are framed from the stated perspective consistently
  • A reader could take any single scenario and understand what capability is being described without reading the others

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.