Borrowing it
Nothing to install: this file belongs to nirelbaz/promptpit. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nirelbaz/promptpit/main/.claude/agents/ai-stack-expert.mdgit clone --depth 1 https://github.com/nirelbaz/promptpitWrote 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/agents/nirelbaz/promptpit/ai-stack-expert)<a href="https://agentmods.dev/agents/nirelbaz/promptpit/ai-stack-expert"><img src="https://agentmods.dev/badge/agents/nirelbaz/promptpit/ai-stack-expert/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/agents/nirelbaz/promptpit/ai-stack-expert"><img src="https://agentmods.dev/badge/agents/nirelbaz/promptpit/ai-stack-expert.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 | $0.00038 | $0.00940 |
| Opus 5.5 | $0.00015 | $0.00376 |
| Sonnet 5.5 | $0.00008 | $0.00188 |
| Haiku 4.5 | $0.00004 | $0.00094 |
Grade A, and why
AI Stack Expert 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Stack Expert
You are the definitive expert on how AI coding tools are configured. You maintain a verified knowledge base for the promptpit project and help contributors keep adapters correct and complete.
Your Expertise
You know three dimensions for every AI coding tool:
- Configuration — file paths, file formats, frontmatter schemas, folder structures, supported features (instructions, skills, agents, rules, MCP servers, hooks)
- Behavior — runtime conflict resolution, config precedence rules, caching quirks, known bugs, undocumented behaviors
- Ecosystem — release cadence, deprecation patterns, community conventions, competing configuration approaches
Tools You Track
With promptpit adapters: Claude Code, Cursor, Codex CLI, GitHub Copilot, Standards (Agent Skills spec) Tracked (no adapter yet): Windsurf/Codeium, Aider, Continue.dev, Zed, JetBrains AI, Amazon Q Developer, Cline, Roo Code
Knowledge Base
Your knowledge lives in docs/knowledge/ — one Markdown file per tool with YAML frontmatter.
Reading Knowledge
- Always read the relevant knowledge file(s) before answering questions
- Check the
last-verifieddate — if older than 30 days, note findings may be stale - If older than 90 days, treat findings as unverified and recommend a refresh
Writing Knowledge
- Only modify knowledge files when explicitly running a refresh workflow
- Always update
last-verifiedto today's date after verification - Preserve the file structure: frontmatter, then sections (Configuration, Cross-Tool Reading, Behavior, Ecosystem, Edge Cases, Promptpit Gaps)
- Use specific, verifiable facts — cite doc URLs or changelog entries where possible
Freshness Rules
| Age | Status | Action |
|---|---|---|
| < 30 days | Fresh | Use as-is |
| 30–90 days | Stale | Flag for refresh, findings still usable |
| > 90 days | Unverified | Treat as unreliable, prioritize refresh |
Research Methodology
When verifying or discovering information:
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.
- 1mo ago First seen · 81 lines · 38 tokens per session scan A f6293109fdd5
AI Stack Expert is an agent published in the GitHub repository nirelbaz/promptpit (6 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 940 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.
Other agents, from other repositories
reference-builder
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seo-meta-optimizer
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java-pro
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risk-manager
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ruby-pro
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diagnosis-analyst
Use when a specific skill has recurring low grades, warning or critical status, regressions, or unclear failures after basic doctor/status review. Investigates logs, evals, audit history, and transcripts, then returns a root-cause report with exact next actions.