anti-patterns
Skill112 starsChanged 2 months agoMITView on GitHub
Catalogue of known SDLC anti-patterns that great_cto agents must actively reject when reviewing architecture, plans, code, or post-mortems. Used by architect (pre-impl), pm (planning), senior-dev (impl), l3-support (post-incident).
3 other projects use a version of this.
Adopted by
Most recently taken up by
- NulightJens/skillstheir own version, first seen May 27, 2026
- aubynsamuel/android-dev-skillstheir own version, first seen May 23, 2026
- ffsshhttiikk/opencode-agents-skillstheir own version, first seen Feb 28, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- ffsshhttiikk/opencode-agents-skills★ 2same name
- NulightJens/skills★ 2same name
- aubynsamuel/android-dev-skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository35 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- aesthetic-instrumentSkill
- anydesignSkill
- archetype-review-baseSkill
- brainstormingSkill
- build-speedSkill
- codex-hostSkill
- committed-aestheticSkill
- cost-modelSkill
- crystallizeSkill
- decision-evalSkill
- deploy-landedSkill
- discoverySkill
- done-blockedSkill
- great_ctoSkill
- lifecycle-messagingSkill
- migration-ready-schemaSkill
- observability-baselineSkill
- opportunity-solution-treeSkill
- outcome-roadmapSkill
- pm-planningSkill
- pre-mortemSkill
- product-economicsSkill
- prose-styleSkill
- quant-validationSkill
- secrets-rotationSkill
- signing-preflightSkill
- skeptical-triageSkill
- stack-baselineSkill
- test-strategySkill
- ui-ux-pro-maxSkill
- vertical-onboardingSkill
- verticalsSkill
- well-architectedSkill
The file
We split this skill into the rules it gives an agent
8 rules. 0 are common, 8 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
8
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 34
Why bad: All cost of distributed (latency, eventual consistency, ops overhead) with none of the benefits (independent deploy, isolation).
- Distinctive: line 47
Fix: Start simple. Optimize when you have load data.
- Distinctive: line 53
Fix: Ask "what's the simplest thing that could work?"
- Distinctive: line 72
Why bad: If wrong, recovery is days or weeks.
- Distinctive: line 122
Fix: Every image has a named source — generated for this product, owned, or licensed — and is served from the product's own assets.
- Distinctive: line 133
Smell: Every error pages. Engineers stop reading alerts.
- Distinctive: line 149
When you find one of these in a proposal/review:
- Distinctive: line 154
If the user disagrees, capture as ADR with the alternatives section filled in
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
SDLC anti-patterns to reject
Reference catalogue. Cite the anti-pattern by name when blocking a proposal — gives the user a clear vocabulary to discuss the issue.
Architecture anti-patterns
A-1. God service
Smell: One service does auth, billing, search, file storage, and email. Why bad: Single deploy unit, single point of failure, every team touches it, change velocity drops over time. Fix: Split by business capability (DDD bounded context).
A-2. Distributed monolith
Smell: 12 microservices but they share a database and deploy together. Why bad: All cost of distributed (latency, eventual consistency, ops overhead) with none of the benefits (independent deploy, isolation). Fix: Either truly separate (own DB, own deploy pipeline) or merge.
A-3. Synchronous chains
Smell: Request → Service A → Service B → Service C → Service D. Why bad: Compound failure probability, p99 latency adds up. Fix: Async with events, or co-locate hot path.
A-4. Premature optimization
Smell: Custom Redis Lua scripts, hand-tuned binary protocols, before the first paying user. Why bad: Complexity cost paid up front, never recouped. Fix: Start simple. Optimize when you have load data.
A-5. Resume-driven development
Smell: "Let's use Kubernetes / GraphQL / event sourcing / DDD" with no current pain it solves. Why bad: Optimizes for engineer's resume, not user's outcome. Fix: Ask "what's the simplest thing that could work?"
Plan / process anti-patterns
P-1. Big-bang rewrite
Smell: "Let's rewrite this in <new framework>."
Why bad: 80% of rewrites fail. The old system has years of bug fixes
baked in.
Fix: Strangler-fig. New behaviour in new code, old code coexists,
delete when traffic moves.
P-2. Hero culture
Smell: "Senior X always fixes the 3am incidents." Why bad: Bus factor 1. X burns out. Knowledge doesn't transfer. Fix: Runbooks, post-mortems, rotating on-call, pair-debugging.
P-3. No reversibility plan
Smell: Plan ships a one-way door (data migration, public API change, breaking-contract release). Why bad: If wrong, recovery is days or weeks. Fix: Mandate dry-run + rollback path before approval.
P-4. Plan without timeboxes
Smell: Tasks named "implement feature X" with no end criteria. Why bad: Open scope, time inflates to fit. Fix: Each task ≤ 4 hours, with explicit "done = X" criteria.
Code-level anti-patterns
C-1. God class / God function
Smell: A class > 500 lines or function > 100 lines doing 5 unrelated things. Why bad: Tests become integration tests. Diff readability collapses. Fix: Single responsibility. Extract collaborators.
C-2. Stringly typed
Smell: Status passed as strings ("open", "closed", "blocked") with no enum. Why bad: Typos compile. New status forgotten in switch. Fix: Enum / discriminated union / branded type.
C-3. Catch-and-continue
Smell:
try { doThing(); } catch (e) { console.log(e); }Why bad: Hides bugs. Silent corruption. Fix: Catch only what you can handle; re-throw the rest; log with context.
C-4. Hardcoded secrets
Smell: API keys, passwords, DB URLs in source.
Why bad: Leaks in git history forever; rotation requires force-push (impossible).
Fix: Env vars or secret manager. Pre-commit hook to grep for sk-, ghp_, etc.
UI anti-patterns
Taken from Google AI Studio's guide to polishing generated interfaces (2026-09-16): the fastest way to spot one is decoration that means nothing.
U-1. Chips that mean nothing
Smell: Status pills, badges, counters and tags that no state drives — "New", "Beta", "AI", "3 insights" on a screen where nothing is new, beta, or counted. Why bad: The reader cannot tell signal from ornament, so a real warning in the same visual language is ignored. It is the most reliable tell of a generated UI. Fix: Each chip names its meaning and the state behind it, or it is removed.
U-2. Placeholder imagery
Smell: Grey boxes, lorem photos, broken or hotlinked stock image URLs in a build that is meant to be shown. Why bad: The first impression is of an unfinished product; hotlinked assets break or change without notice and may not be licensed. Fix: Every image has a named source — generated for this product, owned, or licensed — and is served from the product's own assets.
Incident / ops anti-patterns
O-1. No SLO
Smell: "Production seems slow today" but no SLO target. Why bad: Can't tell breach from normal. Fix: Set p99 latency, error rate, availability SLOs. Track burn.
O-2. Alert spam
Smell: Every error pages. Engineers stop reading alerts. Why bad: Real incidents get missed in noise. Fix: Page only on user-visible failure. Other signals to dashboard, not pager.
O-3. Post-mortem blame
Smell: "Engineer X deployed without testing." Why bad: Suppresses future post-mortems. Blame doesn't fix the system. Fix: Blameless post-mortems. Focus on missing guardrails, not the human.
O-4. Snowflake servers
Smell: "Don't reboot SRV-PROD-3, it has special config that's not in IaC." Why bad: Disaster recovery impossible. Fix: Everything in IaC. Servers are cattle, not pets.
How to use this catalogue
When you find one of these in a proposal/review:
- Cite the code (A-3, P-1, etc.) so the user has a vocabulary
- Quote the specific smell from the proposal
- Propose the specific fix
- If the user disagrees, capture as ADR with the alternatives section filled in
When NOT to apply
- Hobby projects, learning exercises — anti-patterns are about scale
- Throwaway code with explicit
// TODO delete in 2 weeks - Time-boxed POCs where the goal is "does the API actually work"
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

