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.
npx skills add krishagel/geoffrey --skill pai-monitorgit clone --depth 1 https://github.com/krishagel/geoffreyWrote 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.
[](https://agentmods.dev/skills/krishagel/geoffrey/pai-monitor)<a href="https://agentmods.dev/skills/krishagel/geoffrey/pai-monitor"><img src="https://agentmods.dev/badge/skills/krishagel/geoffrey/pai-monitor/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.
<a href="https://agentmods.dev/skills/krishagel/geoffrey/pai-monitor"><img src="https://agentmods.dev/badge/skills/krishagel/geoffrey/pai-monitor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00037 | $0.01343 |
| Opus 5 | $0.00018 | $0.00672 |
| Sonnet 5 | $0.00007 | $0.00269 |
| Haiku 4.5 | $0.00004 | $0.00134 |
Grade A, and why
pai-monitor 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PAI Monitor
Monitor the Personal AI Infrastructure repository and identify opportunities to improve Geoffrey.
Focus Areas
When invoked with an argument, focus analysis on that area:
- packs - Deep dive on PAI pack additions/changes
- hooks - Hook system evolution and patterns
- skills - Skill structure and patterns
- patterns - Architectural patterns (memory, validation, etc.)
Without an argument, perform full analysis across all areas.
Phase 1: Fetch PAI Current State
1.1 Core Documentation
Fetch these from github.com/danielmiessler/Personal_AI_Infrastructure:
README.md- Overall structure and philosophyCLAUDE.md- System instructions and principles- Check releases for version info
1.2 Pack Structure
Explore the Packs/ directory:
- List all available packs
- Sample key packs: hooks, algorithm, memory, skills
- Note any new packs since last analysis
1.3 Recent Changes
- Check recent commits for significant updates
- Look for new patterns or breaking changes
- Note any announcements or migration guides
Phase 2: Analyze Geoffrey Current State
2.1 Core Architecture
Read these Geoffrey files:
CLAUDE.md- Founding principles and guidelinesREADME.md- Current capabilities.claude-plugin/plugin.json- Version info
2.2 Skills Inventory
# Glob for all skills
skills/*/SKILL.md
Create inventory of current skills and their purposes.
2.3 Pattern Identification
Identify Geoffrey's current patterns:
- Hook system usage
- Knowledge storage approach
- Skill structure conventions
- Validation patterns
Phase 3: Gap Analysis
Compare Geoffrey against PAI across these dimensions:
3.1 Pack/Skill Coverage
- What PAI packs do we lack equivalent skills for?
- Which packs would provide highest value?
- Are there redundant or outdated skills?
3.2 Architectural Patterns
- Hook system: How does PAI's compare to our hooks.json?
- Memory system: Knowledge persistence patterns
- Validation: Secret prevention, protected files
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.
- 12d ago First seen · 202 lines · 37 tokens per session scan A 3a20eb53c583
pai-monitor is a skill published in the GitHub repository krishagel/geoffrey (6 stars, last pushed 6mo ago), licensed MIT. It adds 37 tokens to every session and 1,343 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…