Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSnpx agentmods add skills/dds-solutions/ai-tadpole-os/tdd-workflowWrote 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/skills/dds-solutions/ai-tadpole-os/tdd-workflow)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/tdd-workflow"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/tdd-workflow.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00021 | $0.00546 |
| Opus 5 | $0.00010 | $0.00273 |
| Sonnet 5 | $0.00004 | $0.00109 |
| Haiku 4.5 | $0.00002 | $0.00055 |
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 4d 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
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / tdd-workflow
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Information drift, legacy terminology, or documentation mismatch.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
Test-Driven Development (TDD) Protocol
Philosophy: Write tests first, code second. Prove failure before implementing solutions. Workflow Binding: Used directly during
/test,/create, and/debug.
🎯 Progressive Disclosure & L3 Reference Index
Read REQUIRED TDD rules below; consult deep L3 Reference Guides on demand:
| L3 Reference Guide | Purpose | Trigger / When to Load |
|---|---|---|
references/tdd_patterns_and_cycles.md |
Concrete code cycles, Three Laws of TDD, test smell refactoring | Writing unit tests before implementation |
🔄 1. The RED-GREEN-REFACTOR Cycle
1. 🔴 RED ➔ Write a minimal failing test that defines the expected behavior.
2. 🟢 GREEN ➔ Write the minimum production code required to make the test pass.
3. 🔵 REFACTOR ➔ Clean up code, remove duplication, and optimize while staying green.
📐 2. Core TDD Directives
- Test Names Describe Intent: Use clear behavioral names (
it('rejects expired capability tokens')). - YAGNI (You Aren't Gonna Need It): Do not write speculative code beyond what the failing test demands.
- One Logical Assertion: Keep unit tests focused on a single logical invariant.
🛠️ 3. Execution Commands
# 1. Run watch mode for fast feedback
npm run test -- --watch
# 2. Run backend test suite
cargo test --manifest-path server-rs/Cargo.toml
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 58 lines · 21 tokens per session scan A 174f83825482
tdd-workflow is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 546 once invoked, about $0.0001 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.
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