To be honest, the official superpowers/brainstorming skill already does TDD so well, I don't see that much of a need for this. TDD is definitely the way to go with agentic development.
1) Do you not feel self-conscious or weird about calling this "EvanFlow"? Seems like a lot of people these days are naming their AI tools/skills/whatever after themselves which seems self-absorbed. Either that or they hope that if their thing takes off like OpenClaw did then they'll grab the fame that comes along with it.
2) Why does your TDD flow miss the refactor step of TDD?
Let the guy have something. Free and open source developers work tirelessly for free for years supporting software that billion dollar companies use to make huge profits.
We don't question when scientists name stuff after themselves so why question this? At least he gets some recognition for his work.
1) Do you feel weird asking a question like this? What constructive benefit does it add to any dialogue?
Sometimes it’s helpful to ask oneself what’s the benefit of an answer. I cannot think of any for your question and the way you worded it is a bit cringe. People name things after themselves all the time. It does not matter in the slightest.
"Evenflo is a hundred year old infant feeding brand." Probably named to market its baby bottles and accessories.
Everybody who grew up to listen to Pearl Jam had seen or used an Evenflo pacifier, baby bottle, or car seat. That's one reason the song already sounded so familiar.
The refactor step is the silent casualty in AI-assisted TDD. Once the test is green, Claude optimizes for moving to the next test, not for cleaning up the impl that just passed. An "iterate-until-clean" pass at the end is a different thing: you're refactoring cold code, not refactoring with a freshly-written test as the safety net.
Built this as an opinionated Claude Code development flow based on evidence based practices and what has been working for me while developing professional code.
EvanFlow is a single TDD-driven loop. Say "let's evanflow this" and it walks brainstorm → plan → execute → tdd → iterate → STOP. Real checkpoints at design and plan approval. Never auto-commits, never auto-stages, never proposes integration - every git op is your call.
The three things that actually changed how I work:
1. Vertical-slice TDD. One failing test → minimal impl → next test. Watch each test fail before writing the impl that passes it. (Sounds obvious. Almost no agent does it by default. ~62% of LLM-generated test assertions are wrong per HumanEval research, so testing TDD discipline matters more than the impl discipline.)
2. Embedded grilling at decision points. Before locking a plan: what breaks if a user does X? What's the rollback? What's explicitly out of scope? Catches design flaws while they're still cheap.
3. Iterate-until-clean (hard cap of 5 rounds). Re-read the diff against dead code, naming, the deletion test, assertion correctness, and a Five Failure Modes pass (hallucinated actions, scope creep, cascading errors, context loss, tool misuse). For UI: screenshot via headless Chromium.
For bigger plans with 3+ independent units sharing types, it forks into a parallel coder/overseer orchestration. Integration tests at touchpoints ARE the cohesion contract.
Three install paths: Claude Code plugin marketplace, npx skills add, manual copy. MIT.
I’ve thought of going down the TDD model for LLMs as a way of providing constraints on their behavior. I would think that “vertical slice” TDD would encourage the LLM to start tailoring the tests to the implementation rather than establishing the invariants up front, though. I was considering “horizontal” TDD to force the agent to implement constraints before coding to them.
With no disrespect intended because this is also how I would do it (but I wouldn't publish and name it after myself!) - they didn't read the research. They had the AI that actually created this do that for them.
TDD in 2026? Besides, TDDs main benefit is to come up with a decent architecture for your system… LLMs can already do that if instructed. I don’t see the point of TDD
To be honest, the official superpowers/brainstorming skill already does TDD so well, I don't see that much of a need for this. TDD is definitely the way to go with agentic development.
how?i saw superpowers/brainstorming but never saw tdd code produced
It’s supposed to do this, but I’ve found it doesn’t always do it
EvanFlow - thoughts arrive like butterflies?
Oh, he don't know, so he chases them away
Oooohhhh
Seeeethinnggg tests failing not complete... again
Someday soon he'll begin his life again
Two questions
1) Do you not feel self-conscious or weird about calling this "EvanFlow"? Seems like a lot of people these days are naming their AI tools/skills/whatever after themselves which seems self-absorbed. Either that or they hope that if their thing takes off like OpenClaw did then they'll grab the fame that comes along with it.
2) Why does your TDD flow miss the refactor step of TDD?
Let the guy have something. Free and open source developers work tirelessly for free for years supporting software that billion dollar companies use to make huge profits.
We don't question when scientists name stuff after themselves so why question this? At least he gets some recognition for his work.
1) Do you feel weird asking a question like this? What constructive benefit does it add to any dialogue?
Sometimes it’s helpful to ask oneself what’s the benefit of an answer. I cannot think of any for your question and the way you worded it is a bit cringe. People name things after themselves all the time. It does not matter in the slightest.
I initially thought it was a pun on Pearl Jam's classic "Even Flow", then I read your comment and noticed the username... Sad.
I feel like 1 is a self correcting problem. If this goes nowhere it will soon be forgotten.
I can think of one example that did go somewhere: Linux.
TanStack was started by a guy named Tanner
Debian is a portmanteau of Debra (Ian's girlfriend) and Ian.
I don't mind it. It's just a name
Debian is an even better example
ReiserFS is another one that comes to mind.
And djb (the djb) also wrote djbdns.
There are plenty of examples, usually when it coincides with someone’s first project.
Linus did not name it Linux himself: https://en.wikipedia.org/wiki/Linux#Naming
He merely laundered it through a coworker.
Feels like a bonus to me.
Ref 1, he should have called it Daughter.
No Code, surely?
"Evenflo is a hundred year old infant feeding brand." Probably named to market its baby bottles and accessories.
Everybody who grew up to listen to Pearl Jam had seen or used an Evenflo pacifier, baby bottle, or car seat. That's one reason the song already sounded so familiar.
The refactor step is the silent casualty in AI-assisted TDD. Once the test is green, Claude optimizes for moving to the next test, not for cleaning up the impl that just passed. An "iterate-until-clean" pass at the end is a different thing: you're refactoring cold code, not refactoring with a freshly-written test as the safety net.
Built this as an opinionated Claude Code development flow based on evidence based practices and what has been working for me while developing professional code.
EvanFlow is a single TDD-driven loop. Say "let's evanflow this" and it walks brainstorm → plan → execute → tdd → iterate → STOP. Real checkpoints at design and plan approval. Never auto-commits, never auto-stages, never proposes integration - every git op is your call.
The three things that actually changed how I work:
1. Vertical-slice TDD. One failing test → minimal impl → next test. Watch each test fail before writing the impl that passes it. (Sounds obvious. Almost no agent does it by default. ~62% of LLM-generated test assertions are wrong per HumanEval research, so testing TDD discipline matters more than the impl discipline.)
2. Embedded grilling at decision points. Before locking a plan: what breaks if a user does X? What's the rollback? What's explicitly out of scope? Catches design flaws while they're still cheap.
3. Iterate-until-clean (hard cap of 5 rounds). Re-read the diff against dead code, naming, the deletion test, assertion correctness, and a Five Failure Modes pass (hallucinated actions, scope creep, cascading errors, context loss, tool misuse). For UI: screenshot via headless Chromium.
For bigger plans with 3+ independent units sharing types, it forks into a parallel coder/overseer orchestration. Integration tests at touchpoints ARE the cohesion contract.
Three install paths: Claude Code plugin marketplace, npx skills add, manual copy. MIT.
Please don’t post AI generated comments :(
Just write it yourself. I promise it’s worth it
He's even being cheeky by intentionally replacing the em-dash by a regular dash, haha
It's quite well done really, but the cadence...
No x. No y. No z. Just abc.
Its like nails on a chalkboard...
I’ve thought of going down the TDD model for LLMs as a way of providing constraints on their behavior. I would think that “vertical slice” TDD would encourage the LLM to start tailoring the tests to the implementation rather than establishing the invariants up front, though. I was considering “horizontal” TDD to force the agent to implement constraints before coding to them.
Curious, In the repo you mention
> Several rules come from 2025-2026 industry research on agentic coding failure modes
What are some of the papers you read?
With no disrespect intended because this is also how I would do it (but I wouldn't publish and name it after myself!) - they didn't read the research. They had the AI that actually created this do that for them.
> execute → tdd
How are these separate steps?
TDD is how you execute, not something you tack on afterwards.
superpowers/brainstorming is doing TDD as well.
How does this handle “dumb zone” evasion while looping?
https://www.evenflo.com/
TDD in 2026? Besides, TDDs main benefit is to come up with a decent architecture for your system… LLMs can already do that if instructed. I don’t see the point of TDD
I've always been hesitant to prescribe TDD to _everything_ until agentic coding agents came along. TDD is a great way to keep them on track.