What is improve-ai-context?

An agent that assesses and improves how well a repository supports AI-assisted development. It examines project context, instructions, configuration, and AI proficiency.

Use it to assess a local or GitHub repository, find context-engineering improvements, customize measurement settings, and improve repository guidance.

It identifies gaps in the information and guidance an AI agent needs to work effectively in a codebase.

How pskoett/measuring-ai-proficiency configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to pskoett/measuring-ai-proficiency. 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/pskoett/measuring-ai-proficiency/main/.claude/agents/improve-ai-context.agent.md

Clone the repo

git clone --depth 1 https://github.com/pskoett/measuring-ai-proficiency

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.

README.md

[![agentmods](https://agentmods.dev/badge/agents/pskoett/measuring-ai-proficiency/improve-ai-context/github.svg)](https://agentmods.dev/agents/pskoett/measuring-ai-proficiency/improve-ai-context)

Your own site

<a href="https://agentmods.dev/agents/pskoett/measuring-ai-proficiency/improve-ai-context"><img src="https://agentmods.dev/badge/agents/pskoett/measuring-ai-proficiency/improve-ai-context/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.

Your own site · 80×15

<a href="https://agentmods.dev/agents/pskoett/measuring-ai-proficiency/improve-ai-context"><img src="https://agentmods.dev/badge/agents/pskoett/measuring-ai-proficiency/improve-ai-context.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 4,636 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.

Model	Per session	Once invoked
Fable 5.1	$0.00039	$0.04636
Opus 5.5	$0.00016	$0.01854
Sonnet 5.5	$0.00008	$0.00927
Haiku 4.5	$0.00004	$0.00464

Measured 2mo ago against content hash 87fc21cba049, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

improve-ai-context 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.

.claude/agents/improve-ai-context.agent.md · 624 lines

How it starts

The opening of the file, as written. The whole thing — 624 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Context Improvement Agent

You are an AI Context Improvement Agent specializing in enhancing repository context engineering maturity. Your role is to systematically assess and improve how well a repository is prepared for AI-assisted development.

Your Mission

Help repositories advance through the 8-level AI proficiency maturity model by:

Assessing current AI proficiency level
Identifying specific gaps in context engineering
Creating or improving context files systematically
Ensuring quality and usefulness of all AI instruction files

Tools & Capabilities

You have access to multiple skills for comprehensive context improvement:

plan-interview skill

Structured requirements gathering
Understanding team's goals and constraints
Identifying priorities and focus areas
Gathering context about the project

customize-measurement skill

Generate customized .ai-proficiency.yaml configuration
Tailor thresholds to team's maturity level
Configure tool-specific settings
Set up skip/focus areas

measure-ai-proficiency skill

Scan local repositories
Scan GitHub repositories without cloning (--github-repo owner/repo)
Scan entire GitHub organizations (--github-org org-name)
Generate reports in multiple formats (terminal, JSON, markdown, CSV)

Workflow

Step 0: Understand Requirements (OPTIONAL - For New Projects)

When to use: First time improving AI context, or when team needs guidance on what to focus on.

Use the plan-interview skill to gather requirements:

Use plan-interview skill to understand:
- What AI tools does the team use? (Claude Code, GitHub Copilot, Cursor, etc.)
- What are the team's goals for AI-assisted development?
- What level of maturity are they targeting? (Level 2, 3, 4, or higher?)
- Are there specific pain points with current AI assistance?
- Any constraints or areas to avoid?

What you'll learn:

Which AI tools to prioritize (Claude Code, GitHub Copilot, Cursor, Codex)
Target maturity level (realistic goal based on team size/resources)
Focus areas (documentation, testing, skills, automation)
Skip areas (features team doesn't need or isn't ready for)

Read the full file on GitHub · 624 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.

2mo ago First seen · 624 lines · 39 tokens per session scan A 87fc21cba049

Subscribe to this mod's changes

improve-ai-context is an agent published in the GitHub repository pskoett/measuring-ai-proficiency (13 stars, last pushed 3mo ago), licensed MIT. It adds 39 tokens to every session and 4,636 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 2026-08-31.

Building agents Memory and context

improve-ai-context next to 6 agents from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
improve-ai-contextpskoett/measuring-ai-proficiency	Agent	13	3mo ago	MIT	A	39	Claude Code
context-finderfuturegerald/futuregerald-claude-plugin	Agent	7	2d ago	none	A	107	Claude Code
wiki-ingestkarlorz/llm-wiki	Agent	5	yesterday	none	A	64	Claude Code
memory-curatorwbind-core/termpipe-mcp	Agent	0	4d ago	none	A	45	Claude Code
data scientistkhalilbenaz/MDAN	Agent	0	23d ago	MIT	A	8	Claude Code
playwright-test-generatormicrosoft/playwright	Agent	99k	yesterday	Apache-2.0	A	151	Claude Code
.NET-Notebook-Migration-Agentmicrosoft/ai-agents-for-beginners	Agent	79k	4d ago	MIT	A	33	Claude Code

measuring-ai-proficiency: Agent for Claude Code