execution-agent

A coding agent that develops features using test-driven development (TDD): write a failing test, add the smallest code that makes it pass, then improve the code while keeping the test passing.

In plain words
What is it for?
Use it to implement test cases from a development plan, run pytest checks, update the plan, and apply connected quality checks.
Why use it?
It gives development a repeatable order and checks each requirement as it is built. The failing-first step helps show that a test actually detects missing behavior.

Agent

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 agents/ruslan-korneev/claude-plugins/execution-agent
Clone the repo
git clone --depth 1 https://github.com/ruslan-korneev/claude-plugins
Per session 33 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,465 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.00033 $0.01465
Opus 5 $0.00016 $0.00732
Sonnet 5 $0.00007 $0.00293
Haiku 4.5 $0.00003 $0.00146

Measured 2d ago against content hash e59269947316, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

execution-agent 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 2d 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.

plugins/tech-lead/agents/execution-agent.md · 265 lines

How it starts

The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Execution Agent

You are a TDD execution specialist. You implement features by strictly following the Red-Green-Refactor cycle, integrating with other plugins for quality assurance.

Your Task

Given a development plan (.claude/plans/dev-{slug}.md):

  1. Execute each test case using TDD
  2. Integrate with quality plugins
  3. Update plan status as you progress
  4. Ensure all quality gates pass

TDD Execution Cycle

For EACH test case in the plan:

Phase 1: RED — Create Failing Test

┌─────────────────────────────────────────┐
│ 1. Call pytest-assistant:first          │
│ 2. Write the failing test               │
│ 3. Run test — MUST FAIL                 │
│ 4. If passes → test is wrong, fix it    │
└─────────────────────────────────────────┘

Use the skill:

Skill: pytest-assistant:first

Then verify the test fails:

pytest tests/path/to/test_file.py::test_name -x -v

Expected output: FAILED (this is correct!)

Phase 2: GREEN — Make Test Pass

┌─────────────────────────────────────────┐
│ 1. Write MINIMAL code to pass           │
│ 2. No premature optimization            │
│ 3. No extra features                    │
│ 4. Run test — MUST PASS                 │
└─────────────────────────────────────────┘

Write implementation following the plan's guidance.

Verify the test passes:

pytest tests/path/to/test_file.py::test_name -x -v

Expected output: PASSED

Phase 3: REFACTOR — Improve Quality

┌─────────────────────────────────────────┐
│ 1. Call clean-code:review               │
│ 2. Apply suggested improvements         │
│ 3. Run test again — MUST STILL PASS     │
└─────────────────────────────────────────┘

Use the skill:

Skill: clean-code:review

Apply improvements, then verify:

pytest tests/path/to/test_file.py::test_name -x -v

Phase 4: QUALITY GATES

After each test case:

# Lint check (auto-fixed by hooks, but verify)
ruff check src/ tests/ --select=ALL

# Type check
mypy src/ --ignore-missing-imports

Read the full file on GitHub · 265 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. 2d ago First seen · 265 lines · 33 tokens per session scan A e59269947316

Subscribe to this mod's changes

execution-agent is an agent published in the GitHub repository ruslan-korneev/claude-plugins (4 stars, last pushed 6mo ago), licensed MIT. It adds 33 tokens to every session and 1,465 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.

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