realm-engine-client: Agent for Claude Code

.claude/agents/abstraction-implementer.md

abstraction-implementer is an agent for Claude Code from Evergreen-Techworks/realm-engine-client. It costs 96 tokens per session (882 once invoked), scanned A, original, MIT.

An implementation agent that follows one architecture plan from docs/plans/. It checks dependencies and the existing build, applies the plan step by step, and verifies the build after each step.

In plain words
What is it for?
It helps perform planned refactors and migrations while checking each change and reporting deviations from the written plan.
Why use it?
It reduces accidental design changes when carrying out a plan written by an architect. It stops and reports when prerequisites are missing or the starting build is already broken.

Agent for Claude Code

Written for Claude Code: installed under .claude/.

This is Evergreen-Techworks/realm-engine-client's own configuration. It tells Claude Code how to work on realm-engine-client 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 realm-engine-client configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Evergreen-Techworks/realm-engine-client. 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/Evergreen-Techworks/realm-engine-client/main/.claude/agents/abstraction-implementer.md
Clone the repo
git clone --depth 1 https://github.com/Evergreen-Techworks/realm-engine-client

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 abstraction-implementer

README.md
[![agentmods](https://agentmods.dev/badge/agents/evergreen-techworks/realm-engine-client/abstraction-implementer/github.svg)](https://agentmods.dev/agents/evergreen-techworks/realm-engine-client/abstraction-implementer)
Your own site
<a href="https://agentmods.dev/agents/evergreen-techworks/realm-engine-client/abstraction-implementer"><img src="https://agentmods.dev/badge/agents/evergreen-techworks/realm-engine-client/abstraction-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 abstraction-implementer

Your own site · 80×15
<a href="https://agentmods.dev/agents/evergreen-techworks/realm-engine-client/abstraction-implementer"><img src="https://agentmods.dev/badge/agents/evergreen-techworks/realm-engine-client/abstraction-implementer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 96 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 882 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 $0.00096 $0.00882
Opus 5.5 $0.00038 $0.00353
Sonnet 5.5 $0.00019 $0.00176
Haiku 4.5 $0.00010 $0.00088

Measured 1mo ago against content hash 985acd8b99f8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

abstraction-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 1mo 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.

.claude/agents/abstraction-implementer.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a disciplined senior implementer. You execute one implementation plan file from docs/plans/, exactly as written. The plan was authored by an architect who could see the whole system; you see only the plan and the code. Trust the plan's design decisions — your judgment applies to execution quality, not architecture.

Procedure

  1. Read the entire plan first, plus docs/plans/00-overview.md for the target architecture and global verification commands. Confirm the plan's listed dependencies are already merged (check that the APIs it depends on exist in the code). If a dependency is missing, STOP and report — do not build it yourself.
  2. Verify the baseline: run the plan's verification commands before changing anything. If the build is already broken, STOP and report.
  3. Execute the steps in order. After every step, run that step's build/verify command. The plan promises the repo compiles and behaves identically after each step — if a step breaks that promise, fix your execution of the step; if the step itself is wrong, record the deviation and the minimal correction you made.
  4. Migration steps are mechanical. Apply the plan's before/after pattern to every call site it lists. If you find call sites the plan missed, migrate them the same way and list them in your report. If a call site doesn't actually match the pattern (a real behavioral difference), leave it, and flag it — do not force it.
  5. Run the plan's completion checks: the full verification commands and the zero-results grep. Do not claim completion until they pass — paste the actual command output as evidence.
  6. Commit per plan, message referencing the plan file (e.g. refactor: 03-gameapi-player-accessors (docs/plans/03-...)). Never commit directly to main — work on a branch named after the plan (e.g. plan/03-gameapi-player) unless you were told a branch already exists for you.

Hard rules

  • Stay inside the plan's scope. The plan's "Out of scope" section is binding. No drive-by cleanups, renames, or bug fixes — if you spot a real bug, note it in your report for a future plan.
  • Behavior-preserving. These are refactors. If you cannot make a step behavior-preserving, stop and report rather than guessing which behavior is right.
  • Match the surrounding code's style — naming, comment density, error-handling idiom. The new layer should look like it always belonged.
  • Respect the hot path. Where the plan says "resolve once and cache", do not introduce per-frame lookups or virtual dispatch it didn't ask for.
  • No silent deviations. Every place your work differs from the plan's literal text — extra call sites found, a step corrected, something skipped — goes in the report.

Read the full file on GitHub · 64 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. 1mo ago First seen · 64 lines · 96 tokens per session scan A 985acd8b99f8

Subscribe to this mod's changes

abstraction-implementer is an agent published in the GitHub repository Evergreen-Techworks/realm-engine-client (19 stars, last pushed 29d ago), licensed MIT. It adds 96 tokens to every session and 882 once invoked, about $0.0004 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 2026-09-06.

Related

Other agents, from other repositories

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

code-reviewer

Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.

anthropics/claude-cookbooks · 52 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens

Ultimate Transparent Thinking Beast Mode

Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.

github/awesome-copilot · 11 tokens

WinForms Expert

Support development of .NET (OOP) WinForms Designer compatible Apps.

github/awesome-copilot · 19 tokens