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react-agent-pattern: Skill for Cursor

.cursor/skills/tdd-agent-loops/SKILL.md

tdd-agent-loops is a skill for Cursor from vpeetla-ai/react-agent-pattern. It costs 48 tokens per session (353 once invoked), scanned A, a copy of tdd-agent-loops, MIT.

A test-driven development guide for software agents built as graphs, where nodes perform steps and routing chooses what happens next. TDD means writing a failing test, making it pass with the smallest change, then improving the code.

In plain words
What is it for?
Use it to test agent nodes, routing decisions, complete graphs, asynchronous code, and repository-changing workflows with mocked language-model responses and temporary fixture repositories.
Why use it?
It helps find broken routing and loop behavior without relying on real language-model calls, which can be slow or unpredictable in tests.

Skill for Cursor

Written for Cursor: installed under .cursor/.

This is vpeetla-ai/react-agent-pattern's own configuration. It tells Cursor how to work on react-agent-pattern itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything react-agent-pattern configures →

not rated 2repo 2mo ago A scan 48 tokens copy · 100% MIT
View source ↗ vpeetla-ai/react-agent-pattern react-agent-pattern.vercel.app
Reuse

Borrowing it

Nothing to install: this file belongs to vpeetla-ai/react-agent-pattern. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/vpeetla-ai/react-agent-pattern/main/.cursor/skills/tdd-agent-loops/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/vpeetla-ai/react-agent-pattern

Made for: Cursor.

Wrote this? Show the measurements

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README.md
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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.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/vpeetla-ai/react-agent-pattern/tdd-agent-loops"><img src="https://agentmods.dev/badge/skills/vpeetla-ai/react-agent-pattern/tdd-agent-loops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 353 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% 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 5.1 $0.00048 $0.00353
Opus 5.5 $0.00019 $0.00141
Sonnet 5.5 $0.00010 $0.00071
Haiku 4.5 $0.00005 $0.00035

Measured 2mo ago against content hash 26c8e7ebe7c5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 2mo 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

100% identical to tdd-agent-loops — 0 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.

.cursor/skills/tdd-agent-loops/SKILL.md · 54 lines

What it actually says

TDD for Agent Loops

Inspired by mattpocock/skills tdd — adapted for LangGraph.

Red → Green → Refactor

  1. Red — Write failing test for routing or node output (mock LLM)
  2. Green — Minimal node/routing fix
  3. Refactor — Extract helpers only when second test needs it

What to test

Layer Test
Routing route_after_quality returns retry/pass/escalate
Nodes Given state in, partial state out (no real LLM)
Integration Full graph with FakeLLM fixture
Repo-fix Clone fixture repo, assert branch + patch count

Fixtures

@pytest.fixture
def fake_llm():
    return FakeLLM(responses=[{"content": "..."}])

Async

@pytest.mark.asyncio
async def test_graph_happy_path(tmp_path):
    ...

Avoid

  • Tests that only assert "graph compiles"
  • Snapshotting full LLM prose (flaky)
  • Hitting live Groq in CI

Reference

  • loop-engine-agent-platform/tests/test_repo_fix.py
  • *-agent-pattern/tests/ — minimal pattern coverage
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. 2mo ago First seen · 54 lines · 48 tokens per session scan A 26c8e7ebe7c5

Subscribe to this mod's changes

tdd-agent-loops is a skill published in the GitHub repository vpeetla-ai/react-agent-pattern (2 stars, last pushed 2mo ago), licensed MIT. It adds 48 tokens to every session and 353 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to tdd-agent-loops, differing in 0 lines, and is treated as a copy.

Data and AIDebuggingPythonTestingai-agentslanggraphreact-agenttutorial
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