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.
npx agentmods add commands/rosudrag/ai-praxis/tddgit clone --depth 1 https://github.com/rosudrag/ai-praxisWrote 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.
[](https://agentmods.dev/commands/rosudrag/ai-praxis/tdd)<a href="https://agentmods.dev/commands/rosudrag/ai-praxis/tdd"><img src="https://agentmods.dev/badge/commands/rosudrag/ai-praxis/tdd.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00499 |
| Opus 5 | $0.00000 | $0.00249 |
| Sonnet 5 | $0.00000 | $0.00100 |
| Haiku 4.5 | $0.00000 | $0.00050 |
Grade A, and why
tdd 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 6d 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.
What it actually says
/tdd - Test-Driven Development
Guide the implementation of a feature using strict TDD methodology.
Instructions
You are a TDD coach. Every line of production code must be justified by a failing test.
The TDD Cycle
RED → Write a failing test that defines desired behavior
GREEN → Write the minimum code to make the test pass
REFACTOR → Clean up while keeping tests green
REPEAT → Next behavior
Step 1: Understand the Feature
- What behavior is being requested?
- Break it into small, testable increments
- List the test cases in order of implementation
Step 2: Plan the Test Sequence
## TDD Plan: [Feature Name]
### Test Sequence
1. [Simplest happy path case]
2. [Next simplest case]
3. [Edge case]
4. [Error case]
5. [Integration/boundary case]
Step 3: Execute the Cycle
For each test case:
RED Phase:
- Write the test FIRST
- Run it - confirm it FAILS
- Verify it fails for the RIGHT reason (not a syntax error)
GREEN Phase:
- Write the MINIMUM code to pass
- No cleverness - just make the test green
- Run the test - confirm it PASSES
- Run ALL tests - confirm nothing broke
REFACTOR Phase:
- Look for duplication, unclear names, complex logic
- Refactor production code AND test code
- Run all tests after each refactoring step
- Stop when code is clean enough (not perfect)
Step 4: Report Progress
After each cycle, report:
[RED] test_creates_order_with_valid_input - FAILING ✓
[GREEN] test_creates_order_with_valid_input - PASSING ✓
[REFACTOR] Extracted create_order service method
---
[RED] test_rejects_zero_quantity - FAILING ✓
...
Constraints
- NEVER write production code without a failing test first
- NEVER write more than one failing test at a time
- NEVER skip the refactor phase (even if it's "looks good, no changes")
- If a test is hard to write, that's a design signal - simplify the interface
- Run {{test_command}} after EVERY change
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.
- 6d ago First seen · 77 lines · 0 tokens per session scan A 0ac3398aaa33
tdd is a command published in the GitHub repository rosudrag/ai-praxis (2 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 499 tokens. 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 2026-08-31.
Other commands, from other repositories
bugfix
Bug fix workflow: root cause analysis → user review → regression test + fix via TDD.
dashboard
Generar dashboard HTML local con métricas de eficiencia del proyecto SDD.
usage-add
PitWay: Accumulate measured planning or qa token usage onto a milestone.
hub-tdd
TDD workflow for MCP Hub implementation. Types → Tests (red) → Implementation (green) with git gates.
eval
Evaluate and improve one healthcare agent's system prompt. Run up to 5 iterations of: prepare fixed questions -> answer -> judge -> improve -> re-score -> commit if better.
tdd
强制执行测试驱动开发工作流。首先搭建接口,生成测试,然后从实现能通过测试的最小代码。确保 80%+ 的覆盖率。.