test-driven-development

test-driven-development is a skill for Claude Code, Codex from Djtony707/TITAN. It costs 50 tokens per session (3,393 once invoked), scanned A, a copy of test-driven-development, MIT.

A development method in which you write a test that fails, add the smallest code change that makes it pass, and then improve the code while keeping the tests passing. TDD means test-driven development.

In plain words
What is it for?
Adding new logic, fixing bugs, changing existing behavior, covering edge cases, and checking browser-related changes when combined with runtime testing. It is not intended for behavior-free configuration or documentation edits.
Why use it?
It provides evidence that new behavior or a bug fix works instead of relying on code that merely looks correct. Reproducing a bug in a test also helps prevent it from returning.

Skill for Claude CodeCodex

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/djtony707/titan/test-driven-development
Any agent
npx skills add Djtony707/TITAN --skill test-driven-development
Clone the repo
git clone --depth 1 https://github.com/Djtony707/TITAN

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 test-driven-development

README.md
[![agentmods](https://agentmods.dev/badge/skills/djtony707/titan/test-driven-development.svg)](https://agentmods.dev/skills/djtony707/titan/test-driven-development)
Your own site
<a href="https://agentmods.dev/skills/djtony707/titan/test-driven-development"><img src="https://agentmods.dev/badge/skills/djtony707/titan/test-driven-development.svg" alt="Measured on agentmods" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,393 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 84% copy Near-identical to another mod 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 $0.00050 $0.03393
Opus 5 $0.00025 $0.01697
Sonnet 5 $0.00010 $0.00679
Haiku 4.5 $0.00005 $0.00339

Measured 5d ago against content hash 6c60e193d77a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

test-driven-development 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 5d 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.

Origin

This is a copy

84% identical to test-driven-development — 19 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

assets/agent-skills/test-driven-development/SKILL.md · 384 lines

How it starts

The opening of the file, as written. The whole thing — 384 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Test-Driven Development

Overview

Write a failing test before writing the code that makes it pass. For bug fixes, reproduce the bug with a test before attempting a fix. Tests are proof — "seems right" is not done. A codebase with good tests is an AI agent's superpower; a codebase without tests is a liability.

When to Use

  • Implementing any new logic or behavior
  • Fixing any bug (the Prove-It Pattern)
  • Modifying existing functionality
  • Adding edge case handling
  • Any change that could break existing behavior

When NOT to use: Pure configuration changes, documentation updates, or static content changes that have no behavioral impact.

Related: For browser-based changes, combine TDD with runtime verification using Chrome DevTools MCP — see the Browser Testing section below.

The TDD Cycle

    RED                GREEN              REFACTOR
 Write a test    Write minimal code    Clean up the
 that fails  ──→  to make it pass  ──→  implementation  ──→  (repeat)
      │                  │                    │
      ▼                  ▼                    ▼
   Test FAILS        Test PASSES         Tests still PASS

Step 1: RED — Write a Failing Test

Write the test first. It must fail. A test that passes immediately proves nothing.

// RED: This test fails because createTask doesn't exist yet
describe('TaskService', () => {
  it('creates a task with title and default status', async () => {
    const task = await taskService.createTask({ title: 'Buy groceries' });

    expect(task.id).toBeDefined();
    expect(task.title).toBe('Buy groceries');
    expect(task.status).toBe('pending');
    expect(task.createdAt).toBeInstanceOf(Date);
  });
});

Step 2: GREEN — Make It Pass

Write the minimum code to make the test pass. Don't over-engineer:

// GREEN: Minimal implementation
export async function createTask(input: { title: string }): Promise<Task> {
  const task = {
    id: generateId(),
    title: input.title,
    status: 'pending' as const,
    createdAt: new Date(),
  };
  await db.tasks.insert(task);
  return task;
}

Read the full file on GitHub · 384 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. 5d ago First seen · 384 lines · 50 tokens per session scan A 6c60e193d77a

Subscribe to this mod's changes

test-driven-development is a skill published in the GitHub repository Djtony707/TITAN (19 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 3,393 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to test-driven-development, differing in 19 lines, and is treated as a copy.

Related

Other skills, from other repositories

Test Driven Development

Drive behavior changes through a failing test, the smallest working implementation, and then cleanup once the behavior is locked.

agentic-in/elephant-agent · 26 tokens

test-driven-development

TDD: enforce RED-GREEN-REFACTOR, tests before code.

StarryCod/cogitum · 20 tokens

edgeone skill scanner

Scan any agent skill for security risks before you install or use it. Powered by Tencent Zhuque Lab A.I.G (AI-Infra-Guard). 100% local static analysis — no file contents or credentials leave your device. Compatible with CodeBuddy, Cursor, Windsurf, Claude Code, OpenClaw and more. Triggers on: 这个 skill 安全吗, skill 安全扫描…

Tencent/AI-Infra-Guard · 148 tokens

continual-learning

Nightly refinement of an existing per-repo review-style prompt using this reviewer's own finding outcomes. Read confirmed (resolved-by-commit / thumbs-up) and dismissed (thumbs-down) findings, promote the bug patterns the team actually fixes, demote the false-positive patterns, reconcile against the current prompt…

langchain-ai/open-swe · 89 tokens

nano-banana-pro-openrouter

Deterministic OpenRouter image generation adapter for Nano Banana Pro / Gemini image models. Use as skillexec when a meta-skill needs local image files and structured IMAGEREADY records without spawning an LLM agent.

opensquilla/opensquilla · 49 tokens

skill-creator-linter

Internal tool (not user-invocable). Called by meta-skill-creator as a DAG step (kind: agent) to lint a candidate meta-skill SKILL.md against G1 (parse + reference check + xmlescape grep + structural lint) and G2 (scheduler dry-run with stub executors). Deterministic, sub-second, no LLM. Returns JSON diagnostics.

opensquilla/opensquilla · 84 tokens