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?
"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.
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
Linus started Linux when he was 21, an undergrad at the University of Helsinki. You're entirely welcome to use whatever filtering function for products you use, but it doesn't seem like soley using this particular product's creator's age as a disqualifier comes from a place of sound reasoning, to me.
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?
I can think of one example that did go somewhere: Linux.
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.
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.
Just write it yourself. I promise it’s worth it
> Several rules come from 2025-2026 industry research on agentic coding failure modes
What are some of the papers you read?
How are these separate steps?
TDD is how you execute, not something you tack on afterwards.