tdd-workflow

tdd-workflow is a skill for Claude Code, Codex from phuonghx/aim-cli. It costs 106 tokens per session (1,051 once invoked), scanned A, original, MIT.

A guide to test-driven development (TDD), a method where you write a failing test, add the smallest code that passes it, and then clean up the result.

In plain words
What is it for?
Use it when building features, fixing bugs, or implementing logic with edge cases by working through the red-green-refactor cycle.
Why use it?
It turns expected behavior into an executable specification and gives each change a clear feedback loop. It also helps prevent writing more code than the requirement needs.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/phuonghx/aim-cli/tdd-workflow
Any agent
npx skills add phuonghx/aim-cli --skill tdd-workflow
Clone the repo
git clone --depth 1 https://github.com/phuonghx/aim-cli

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for tdd-workflow

README.md
[![agentmods](https://agentmods.dev/badge/skills/phuonghx/aim-cli/tdd-workflow.svg)](https://agentmods.dev/skills/phuonghx/aim-cli/tdd-workflow)
Your own site
<a href="https://agentmods.dev/skills/phuonghx/aim-cli/tdd-workflow"><img src="https://agentmods.dev/badge/skills/phuonghx/aim-cli/tdd-workflow.svg" alt="Measured on agentmods" height="20"></a>
Per session 106 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,051 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00106 $0.01051
Opus 5 $0.00053 $0.00526
Sonnet 5 $0.00021 $0.00210
Haiku 4.5 $0.00011 $0.00105

Measured 2d ago against content hash 1dd05a749ef0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

tdd-workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

aim/templates/aim-agents/skills/tdd-workflow/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

TDD Workflow

In test-driven development the test comes before the code. You describe the behavior you want as an executable expectation, watch it fail, then write just enough to satisfy it. The test becomes the specification, and a passing suite becomes the proof.

The loop

  ┌─────────────────────────────────────────────┐
  │  RED      write a test; run it; watch it fail │
  │   ↓                                           │
  │  GREEN    write the least code that passes it │
  │   ↓                                           │
  │  REFACTOR tidy up while every test stays green│
  │   ↓                                           │
  └──── repeat for the next behavior ─────────────┘

Three constraints keep the loop honest:

  1. Add production code only in response to a test that is currently failing.
  2. Write no more of a test than it takes to show that failure.
  3. Write no more code than it takes to turn that test green.

RED — start with a failing test

Express what the code should do, never how it does it.

Aim at Example name
Core behavior adds two positive numbers
Boundaries returns zero for an empty list
Failure modes raises on a negative quantity

Ground rules: the test must fail before you write any implementation, its name should read as a sentence about behavior, and each test should pin down a single idea.

# RED — this fails because cart_total does not exist yet
def test_cart_total_sums_line_items():
    cart = Cart(items=[Item(price=300), Item(price=150)])
    assert cart.total() == 450

GREEN — do the minimum to pass

Write the plainest thing that turns the bar green. No speculative features, no tuning.

Principle What it means here
Avoid speculation If a test does not demand it, do not build it
Plainest solution The most obvious code that satisfies the assertion
Defer performance Make it correct now; make it fast later, if measured
# GREEN — just enough to satisfy the test
class Cart:
    def __init__(self, items):
        self.items = items
    def total(self):
        return sum(item.price for item in self.items)

Read the full file on GitHub · 122 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 122 lines · 106 tokens per session scan A 1dd05a749ef0

Subscribe to this mod's changes

tdd-workflow is a skill published in the GitHub repository phuonghx/aim-cli (1 stars, last pushed 2mo ago), licensed MIT. It adds 106 tokens to every session and 1,051 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

ai-observability-promptfoo

Testing and evaluation framework for LLM prompts and applications -- promptfooconfig.yaml, assertions, model-graded evals, red teaming, CI/CD integration, custom providers, and comparative evaluation.

agents-inc/skills · 46 tokens

autonomous-pipeline

Orchestrate the full AIDLC Autonomous Pipeline from a one-sentence requirement to a PR-ready delivery with TDD methodology. DDD drives judgment, SDD produces specs, TDD verifies delivery. Stages: Evaluate, Think, Plan, Build, Review, Test, Deliver, Reflect. Checkpoints on BLOCK or context limits. TRIGGER: "run…

xg-gh-25/SwarmAI · 116 tokens

fable-tdd

Drive testable behavior changes and bug fixes through disciplined red-green-refactor cycles with observable regression tests. Use when implementing new features with unit/integration tests, fixing reproducible bugs, modifying business logic, or writing test-first behavior contracts — even if the user does not…

imMamdouhaboammar/get-fable · 133 tokens

fable-mode

Compatibility alias for the canonical get-fable coding lifecycle. Use when the user explicitly asks for Fable mode or when an existing installation invokes this legacy skill name.

imMamdouhaboammar/get-fable · 36 tokens

orch-tdd

Use when implementing a feature via test-driven development - write a failing test first, get to green with the smallest correct change, then refactor. Enforces vertical slice shape and red-commit-hash evidence.

mattmre/EVOKORE-MCP-PUBLIC · 46 tokens

triage-bug

Use when triaging a bug from session evidence (evidence-capture JSONL, replay JSONL, telemetry, repo-audit) instead of from a live user description, and producing a TDD fix plan plus a docs/bugs/{slug}.md triage artifact.

mattmre/EVOKORE-MCP-PUBLIC · 60 tokens