// Prevent feature creep when building software, apps, and AI-powered products. Use this skill when planning features, reviewing scope, building MVPs, managing backlogs, or when a user says "just one more feature." Helps developers and AI agents stay focused, ship faster, and avoid bloated products.
| name | avoid-feature-creep |
| description | Prevent feature creep when building software, apps, and AI-powered products. Use this skill when planning features, reviewing scope, building MVPs, managing backlogs, or when a user says "just one more feature." Helps developers and AI agents stay focused, ship faster, and avoid bloated products. |
Stop building features nobody needs. This skill helps you ship products that solve real problems without drowning in unnecessary complexity.
Feature creep kills products. It delays launches, burns budgets, exhausts teams, and creates software nobody wants to use. The most successful products do fewer things well.
Feature creep is the gradual accumulation of features beyond what your product needs to deliver value. It happens slowly, then all at once.
Warning signs you're in trouble:
What it costs:
Before adding ANY feature, run through this checklist:
1. VALIDATE THE PROBLEM
□ Does this solve a real, validated user pain point?
□ Have we talked to actual users about this need?
□ What evidence supports building this?
2. CHECK ALIGNMENT
□ Does this support the core product vision?
□ Would this delay our current release?
□ What are we NOT building if we build this?
3. MEASURE IMPACT
□ How will we know if this feature succeeds?
□ What KPIs will change?
□ Can we quantify the value (time saved, revenue, retention)?
4. ASSESS COMPLEXITY
□ What's the true cost (build + test + maintain + document)?
□ Does this add dependencies or technical debt?
□ Can we ship a simpler version first?
5. FINAL GUT CHECK
□ Would we delay launch by a month for this feature?
□ Is this a differentiator or just table stakes?
□ Would removing this harm the core experience?
If you can't answer YES to questions 1-3 with evidence, do not build the feature.
Rule 1: Define and Defend Your MVP
Write down exactly what "done" means before you start. Document what you're NOT building. Reference this constantly.
## MVP Scope Document Template
### Core Problem
[One sentence describing the user problem]
### Success Criteria
[How we know we've solved it]
### In Scope (v1)
- Feature A: [brief description]
- Feature B: [brief description]
### Explicitly Out of Scope
- Feature X: Deferred to v2
- Feature Y: Will not build unless [condition]
- Feature Z: Not our problem to solve
### Non-Negotiables
- Ship by [date]
- Budget: [hours/dollars]
- Core user: [specific persona]
Rule 2: Use Version Control for Scope
Treat scope like code. Track changes. Require approval for additions.
# Create a scope document and track it
git add SCOPE.md
git commit -m "Initial MVP scope definition"
# Any scope changes require explicit commits
git commit -m "SCOPE CHANGE: Added feature X - approved by [stakeholder] - impact: +2 weeks"
Rule 3: The 48-Hour Rule
When someone requests a new feature, wait 48 hours before adding it to the backlog. Most "urgent" requests feel less urgent after reflection.
Rule 4: Budget-Based Scoping
Every feature has a cost. When something new comes in, something else must go out.
"Yes, we can add that. Which of these three features should we cut to make room?"
Saying no to features is a skill. Here are templates:
To stakeholders:
"That's an interesting idea. Based on our user research, it doesn't solve our core user's top three problems. Let's add it to the v2 consideration list and revisit after we validate the MVP."
To executives:
"I understand the value this could bring. If we add this, we'll delay launch by [X weeks] and deprioritize [Y feature]. Here are the trade-offs - which path should we take?"
To users:
"Thanks for the feedback. We're focused on [core problem] right now. I've logged this for future consideration. Can you tell me more about why this would be valuable?"
To yourself:
"Is this scratching my own itch or solving a real user problem? Would I bet the release date on this?"
To AI agents (Claude, Opus, Codex, Ralph, Cursor):
"Stop. Before we add this feature, answer: Does this solve the core user problem we defined at the start of this session? If not, add it to a DEFERRED.md file and stay focused on the current scope."
When working with AI coding agents:
When building AI-powered products, feature creep has extra risks:
AI Feature Creep Red Flags:
AI Feature Discipline:
Before adding any AI feature, answer:
A messy backlog enables feature creep. Clean it ruthlessly.
Monthly Backlog Audit:
For each item older than 30 days:
1. Has anyone asked about this since it was added?
2. Does it still align with current product vision?
3. If we never built this, would anyone notice?
If the answer to all three is "no" → Delete it.
Priority Framework (MoSCoW):
Be honest: Most "Should Haves" are actually "Could Haves" in disguise.
Session Start Check: Before coding with any AI assistant (Claude, Cursor, OpenCode), state:
Mid-Session Check: Every 30-60 minutes, ask your AI: "Are we building the right thing today, or are we adding scope?"
If the answer is "adding scope," stop. Commit what you have. Start fresh.
Session End Check: Before closing an AI coding session:
Daily AI Check: At the end of each day working with AI assistants:
1. Features completed today: [list]
2. Scope additions today: [list]
3. Was each addition validated? [yes/no]
4. Tomorrow's focus: [single item]
Sprint Planning Guard Rails:
Stakeholder Management: Create a single source of truth for scope decisions:
## Scope Decision Log
| Date | Request | Source | Decision | Rationale | Trade-off |
|------|---------|--------|----------|-----------|-----------|
| 2025-01-15 | Add export to PDF | PM | Deferred v2 | Not core to MVP | Would delay launch 2 weeks |
| 2025-01-16 | Dark mode | User feedback | Approved | User research shows demand | Removed social sharing |
| 2025-01-17 | Add caching layer | Claude | Deferred | Premature optimization | Stay focused on core feature |
| 2025-01-17 | Refactor to hooks | Cursor | Rejected | Works fine as is | Technical scope creep |
Agents as Stakeholders: AI coding agents are now stakeholders in your project. They have opinions. They make suggestions. Treat them like any other stakeholder:
Common agent-driven scope creep patterns:
Each of these might be good ideas. None of them are your current scope unless you decide they are.
If feature creep has already happened:
Step 1: Audit Current Features
Step 2: Categorize
Step 3: Remove or Hide
Step 4: Prevent Recurrence
When reviewing any feature request, ask:
1. "What user problem does this solve?"
2. "What's the smallest version we could ship?"
3. "What are we NOT building to make room for this?"
4. "How will we measure success?"
5. "What happens if we never build this?"
If you can't answer these clearly → Do not proceed.
Ship something small that works. Then iterate based on real usage data.
Users don't remember features. They remember whether your product solved their problem.
Every feature you don't build is:
The best products aren't the ones with the most features. They're the ones that do the right things exceptionally well.
"Perfection is achieved not when there is nothing more to add, but when there is nothing left to take away." - Antoine de Saint-Exupéry
Building AI agents with the Convex Agent component including thread management, tool integration, streaming responses, RAG patterns, and workflow orchestration
Guidelines for building production-ready Convex apps covering function organization, query patterns, validation, TypeScript usage, error handling, and the Zen of Convex design philosophy
How to create, structure, and publish self-contained Convex components with proper isolation, exports, and dependency management
Scheduled function patterns for background tasks including interval scheduling, cron expressions, job monitoring, retry strategies, and best practices for long-running tasks
Complete file handling including upload flows, serving files via URL, storing generated files from actions, deletion, and accessing file metadata from system tables
Writing queries, mutations, actions, and HTTP actions with proper argument validation, error handling, internal functions, and runtime considerations