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grafikerdem/agent-context-economy

Analysis updated 2026-05-18

★ 6PowerShellAudience · developerComplexity · 2/5LicenseSetup · easy

TLDR

A PowerShell toolkit and six-layer methodology for reducing the context waste AI coding agents produce when exploring code: fewer lines read, fewer commands run, no repeated searches.

Mindmap

mindmap
  root((agent-context-economy))
    Six Layers
      Continuity
      Repository map
      Discovery
      Targeted reading
      Workflow discipline
      Validation
    Scripts
      repo-map.ps1
      session-state.ps1
      read-symbol.ps1
      run-compact.ps1
    Agents Supported
      Claude Code
      Cursor and Codex
      Windsurf and Copilot
    Benefits
      91 percent less noise
      87 percent less source read
      No external dependencies
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Code map

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filefunction / class

What do people build with it?

USE CASE 1

Install ACE into a Windows repo and configure Claude Code or Cursor to follow the six-layer workflow, cutting context waste during long coding sessions.

USE CASE 2

Use repo-map.ps1 at the start of an agent session to give the AI a compact project overview instead of letting it explore blindly.

USE CASE 3

Wrap noisy test commands with run-compact.ps1 to keep validation output under a line limit without losing the important diagnostics.

USE CASE 4

Use session-state.ps1 to save the current task and relevant file paths between agent sessions so the AI does not start from scratch each time.

What is it built with?

PowerShell

How does it compare?

grafikerdem/agent-context-economynickalaslight/fable-sonnet-orchestrator-kitwoodfishhhh/ez_math_model
Stars6111
LanguagePowerShellPowerShellPowerShell
Setup difficultyeasymoderatemoderate
Complexity2/53/53/5
Audiencedeveloperdeveloperresearcher

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

Windows-only, requires PowerShell 5.1 or later with no other dependencies.

Free to use for any purpose, including commercial use, as long as you keep the copyright notice.

In plain English

This repository is a methodology and toolkit for making AI coding agents work more efficiently. When AI agents like Claude Code, Cursor, or Codex explore a codebase, they often waste their limited conversation context by reading entire large files, dumping long terminal output, or re-discovering the same code repeatedly. This project provides a structured six-layer approach and a set of PowerShell scripts to cut that waste. The six layers are: continuity (carrying forward only the current task and relevant file paths), repository mapping (building a lightweight summary of the project structure at the start), discovery (finding exactly the right files with targeted searches rather than broad exploration), targeted reading (reading only the specific function or line range you need instead of entire files), workflow discipline (starting compactly and moving through bounded steps), and validation (keeping test and build output useful without dumping thousands of lines into the conversation). A benchmark included in the repo shows the practical difference: compared to a conventional workflow, the approach reduced terminal output by 91%, source lines read by 87%, and shell commands issued by 71%. The scripts also include a provenance footer on compacted output so the agent knows what was excluded and why, reducing the risk of hidden selection bias. The toolkit is pure PowerShell with no external dependencies, no Node.js, no Python, no Docker. It is designed for Windows repositories. Installation amounts to running a setup script, copying example policy instructions into your project's agent configuration file (AGENTS.md, CLAUDE.md, or equivalent), and then following the recommended workflow sequence when exploring or modifying code. This is for developers who use AI coding agents frequently and want to reduce how often those agents run out of context, repeat searches, or produce hard-to-read validation output.

Copy-paste prompts

Prompt 1
I have agent-context-economy installed in my Windows repo. Walk me through running setup-ai-scripts.ps1, smoke-test.ps1, and repo-map.ps1, then explain what repo-map.md contains.
Prompt 2
My AI coding agent keeps reading entire large files when it only needs one function. Show me how to use read-symbol.ps1 and read-window.ps1 from agent-context-economy.
Prompt 3
I want to add ACE methodology rules to my CLAUDE.md file. Based on examples/AGENTS.example.md, what are the key policies I should copy in and why?
Prompt 4
My Claude Code session runs out of context after a few searches. Walk me through the ACE workflow (repo-map, investigate, read-symbol, run-compact) for a typical bug-fix task.
Prompt 5
Run the ACE benchmark at scripts/powershell/benchmark.ps1 and explain what each of the three metrics means and why reducing them matters for AI agent efficiency.

Frequently asked questions

What is agent-context-economy?

A PowerShell toolkit and six-layer methodology for reducing the context waste AI coding agents produce when exploring code: fewer lines read, fewer commands run, no repeated searches.

What language is agent-context-economy written in?

Mainly PowerShell. The stack also includes PowerShell.

What license does agent-context-economy use?

Free to use for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is agent-context-economy to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is agent-context-economy for?

Mainly developer.

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