| name | llm-product-discipline |
| description | Intercepts feature requests before coding. Forces product-value, architecture, and cleanup checks so the agent does not generate low-value or hacky features. |
LLM Product Discipline
Purpose
Use this skill before implementing any new feature, enhancement, or prototype.
The goal is to prevent:
- shipping low-value features
- architecture decay
- hacky iterations
- confusing prototypes with real product thinking
Trigger
Use this skill when:
- the user asks to add a feature
- the user asks for a prototype
- the user asks for a quick implementation
- a change touches architecture or existing flows
- the request sounds easy but product value is unclear
Required behavior
Before writing code, do ALL of the following:
Step 1: Restate the request
Summarize the requested feature in 1-2 sentences.
Step 2: Evaluate product value
Answer:
- Who is this for?
- What problem does it solve?
- How painful/frequent is the problem?
- What happens if we do not build it?
- Is this core, leverage, or convenience?
If the request is weak, say so clearly.
Step 3: Evaluate architecture
Answer:
- Does this fit the current design?
- Would implementing it require hacks, duplication, or awkward exceptions?
- Should the design be refactored first?
If refactor is needed, recommend refactor before implementation.
Step 4: Evaluate whether cleanup is higher ROI
Answer:
- Is fixing or simplifying existing code higher value than adding this feature?
- What existing issues should be cleaned first?
Step 5: Give a decision
Choose one:
- BUILD NOW
- REFACTOR FIRST
- DO NOT BUILD YET
Explain why.
Output format
Always respond in this structure before coding:
Feature Summary
...
Value Check
...
Architecture Check
...
Cleanup Check
...
Decision
BUILD NOW / REFACTOR FIRST / DO NOT BUILD YET
If Building
Describe the smallest correct implementation.
Rules
- Do not jump straight into code for feature requests.
- Do not treat “easy to code” as evidence of value.
- Do not patch bad architecture with LLM-generated hacks.
- Prefer fewer, higher-conviction features.
- Leave the system cleaner than you found it.
