Borrowing it
Nothing to install: this file belongs to vpeetla-ai/aegisai-enterprise-agent-platform. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/vpeetla-ai/aegisai-enterprise-agent-platform/main/.cursor/skills/tdd-agent-loops/SKILL.mdgit clone --depth 1 https://github.com/vpeetla-ai/aegisai-enterprise-agent-platformWrote 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/vpeetla-ai/aegisai-enterprise-agent-platform/tdd-agent-loops)<a href="https://agentmods.dev/skills/vpeetla-ai/aegisai-enterprise-agent-platform/tdd-agent-loops"><img src="https://agentmods.dev/badge/skills/vpeetla-ai/aegisai-enterprise-agent-platform/tdd-agent-loops/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vpeetla-ai/aegisai-enterprise-agent-platform/tdd-agent-loops"><img src="https://agentmods.dev/badge/skills/vpeetla-ai/aegisai-enterprise-agent-platform/tdd-agent-loops.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00048 | $0.00353 |
| Opus 5 | $0.00024 | $0.00177 |
| Sonnet 5 | $0.00010 | $0.00071 |
| Haiku 4.5 | $0.00005 | $0.00035 |
Grade A, and why
tdd-agent-loops 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 12d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 12d ago First seen · 54 lines · 48 tokens per session scan A 26c8e7ebe7c5
tdd-agent-loops is a skill published in the GitHub repository vpeetla-ai/aegisai-enterprise-agent-platform (2 stars, last pushed 8d ago), with no licence file. It adds 48 tokens to every session and 353 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
test-audit
Audit test suites for T1-T4 violations using AST analysis, mock detection, and multi-stage synthesis. Invoke when user asks to audit tests, check test quality, find mock violations, review test effectiveness, or inspect test suites for over-mocking. Triggers automatic rewrites when quality gates fail.
代码调试
A debugging workflow that reproduces a problem with a failing test, collects evidence, finds the underlying cause, applies a fix, and runs regression checks. Regression checks verify that the fix does not break behavior that already worked.
代码实现
A coding workflow for checking requirements, understanding existing code, designing module boundaries, writing tests first, implementing changes, and reviewing risks. TDD means writing a failing test, making it pass, then improving the code.
evidence-ledger
An evidence record for completion claims such as “fixed” or “tests passed.” TDD, or test-driven development, is a practice of first seeing a test fail, then making it pass, and checking it again after cleanup.
tdd
The test-first gate. Routed to by /feature (after the spec is approved), /fix, and /refactor before any implementation code is written. Six gated phases — obligation scan, red, green, obligation verify, coverage, lint. No feature code exists before Phase 1 clears; nothing reaches commit-gate until all six are green.
gsd-builder
Implement a design document end-to-end in a target repo by driving Claude Code through the GSD workflow — define a GSD milestone from the doc, then run /gsd-autonomous (TDD, skip-discuss) to build all phases unattended. Use when the operator hands you a design/spec document and asks to autonomously build, implement…