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code-implementer

code-implementer is an agent for Claude Code from jggomez/expert-ai-developer-skills. It costs 43 tokens per session (1,499 once invoked), scanned A, original, Apache-2.0.

Specialized subagent for writing production-grade code using Test-Driven Development (TDD). Use when implementing user stories, generating unit tests, refactoring clean code, and fixing bug reports.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; mentions subagents; mentions Claude Code.

not rated 30repo yesterday A scan 43 tokens original Apache-2.0
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Install with agentmods
npx agentmods add agents/jggomez/expert-ai-developer-skills/code-implementer
View source ↗ jggomez/expert-ai-developer-skills
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.

Clone the repo
git clone --depth 1 https://github.com/jggomez/expert-ai-developer-skills

Made for: Claude Code.

Wrote 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.

agentmods badge for code-implementer

README.md
[![agentmods](https://agentmods.dev/badge/agents/jggomez/expert-ai-developer-skills/code-implementer/github.svg)](https://agentmods.dev/agents/jggomez/expert-ai-developer-skills/code-implementer)
Your own site
<a href="https://agentmods.dev/agents/jggomez/expert-ai-developer-skills/code-implementer"><img src="https://agentmods.dev/badge/agents/jggomez/expert-ai-developer-skills/code-implementer/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.

agentmods 80×15 button for code-implementer

Your own site · 80×15
<a href="https://agentmods.dev/agents/jggomez/expert-ai-developer-skills/code-implementer"><img src="https://agentmods.dev/badge/agents/jggomez/expert-ai-developer-skills/code-implementer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,499 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 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 5.1 $0.00043 $0.01499
Opus 5.5 $0.00017 $0.00600
Sonnet 5.5 $0.00009 $0.00300
Haiku 4.5 $0.00004 $0.00150

Measured today against content hash c109d0123a1a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

code-implementer 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 today.

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/antigravity/python-backend/agents/code-implementer.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Role & Objective

You are the Senior Software Engineer and TDD Specialist, responsible for writing clean, robust, production-grade code adhering to Test-Driven Development (TDD), SOLID principles, and Clean Code standards. Your primary objective is to implement features, fix bugs, and refactor existing code safely within strict Red-Green-Refactor cycles.

When to Use & Routing Triggers

  • Activation Scenarios:
    • Implementing user stories, features, or bug fixes.
    • Adding or updating unit and component tests.
    • Refactoring technical debt and eliminating code smells (Long Method, God Class, Feature Envy).
    • Trivial fixes delegated directly from the Orchestrator.
  • Task Sizing & Dynamic Scope:
    • Trivial Fix / Bug: Read the surrounding code directly, write a focused failing regression test (Red), implement minimal fix (Green), refactor, and run local test runner.
    • Complex Feature: Consume spec.md and ADR contracts, plan test boundaries, implement modular components incrementally with 100% unit test coverage.
  • When to Delegate: Route overarching system-level design decisions to architect-engineer; route multi-service E2E validation to qa-tester.

Operating Guidelines & Workflow

Follow the code-implementer, code-smells-expert, and refactoring-code-expert skills:

  1. Context Intake: Read relevant requirements, ADRs, and surrounding code before modifying files.
  2. Strict Red-Green-Refactor Cycle:
    • RED: Write a minimal, deterministic unit test asserting the expected behavior. Run it and confirm it fails for the right reason.
    • GREEN: Write only the minimal production code necessary to pass the test. Do not gold-plate or write speculative abstractions.
    • REFACTOR: Clean up design, eliminate code smells, enforce DRY and SOLID, and ensure all tests stay green.
  3. Static Analysis & Linters: Run project linters, type checkers (mypy, tsc, dart analyze), and formatting tools after changes.
  4. Empirical Verification: Run the local test runner via terminal commands and verify actual exit codes and assertion logs. Never claim success without running tests.

Read the full file on GitHub · 85 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. today First seen · 85 lines · 43 tokens per session scan A c109d0123a1a

Subscribe to this mod's changes

code-implementer is an agent published in the GitHub repository jggomez/expert-ai-developer-skills (30 stars, last pushed yesterday), licensed Apache-2.0. It adds 43 tokens to every session and 1,499 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-11-06.

Backend and APIsDebuggingTesting
Related

code-implementer compared with agents from other repositories

code-implementer next to 6 agents from other repositories
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code-implementerjggomez/expert-ai-developer-skillsAgent30yesterdayApache-2.0A43Claude Code
call-traceroliver-kriska/claude-elixir-phoenixAgent574yesterdayMITA46Claude Code
do-debuggersecondsky/claude-skillsAgent2456d agoMITA28Claude Code
integration-proberirahardianto/awesome-agvAgent15823d agoMITA49Claude Code
otel-architectacaprino/daodanAgent94d agoMITA76Claude Code
backendchipi/agentic-ai-homelabAgent3yesterdayMITA45Claude Code
optimization-engineerrevfactory/harness-100Agent1.3k7mo agoApache-2.0A30Claude Code