Use when adding new error messages to React, or seeing "unknown error code" warnings.
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 β 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 β 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 β Where does the system parameterize behavior?
- Hardcoded assumptions β Where is the system locked to one implementation?
- Extension patterns β Base classes, registries, plugin directories, strategy patterns
- Domain entities β First-class concepts that could reasonably be added or swapped
For end-user capability perspective:
- User-facing behaviors β What can the user do today?
- Workflow gaps β Where does the user hit dead ends or workarounds?
- Configuration surface β What can/can't the user control?
- Output formats β What forms does data take when presented to users?
For operator workflow perspective:
- Deployment topology β How is the system run?
- Configuration mechanisms β What knobs exist?
- Observability β What can be monitored, what's opaque?
- Recovery paths β What happens on failure?
For security posture perspective:
- Trust boundaries β Where does the system validate input?
- Privilege levels β What access controls exist?
- Data exposure β What sensitive data flows where?
- Attack surface β 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:
- Frame as "{Actor} wants to {action} {target}"
- Note the evidence β what in the codebase or plan revealed this scenario
- Note the current state β 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 β 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:** {β¦}
**Current state:** {β¦}
---
## {Thematic Group 2}
### SCEN-003: {Actor} wants to {action} {target}
**Evidence:** {β¦}
**Current state:** {β¦}
---
{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 β 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.