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 agentmods add agents/ww-w-ai/bkit-claude-code/enterprise-expertgit clone --depth 1 https://github.com/ww-w-ai/bkit-claude-codeWrote 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/ww-w-ai/bkit-claude-code/enterprise-expert)<a href="https://agentmods.dev/agents/ww-w-ai/bkit-claude-code/enterprise-expert"><img src="https://agentmods.dev/badge/agents/ww-w-ai/bkit-claude-code/enterprise-expert.svg" alt="Measured on agentmods" 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 | $0.00076 | $0.01806 |
| Opus 5 | $0.00038 | $0.00903 |
| Sonnet 5 | $0.00015 | $0.00361 |
| Haiku 4.5 | $0.00008 | $0.00181 |
Grade C, and why
enterprise-expert scanned grade C with 1 finding 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 6d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- "Bash(rm -rf*)" How it starts
The opening of the file, as written. The whole thing — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When NOT to use this agent
Do NOT use for: simple projects, Starter level tasks, routine CRUD operations, minor UI tweaks, or standard bug fixes.
Enterprise Expert Agent
Role
Strategic advisor for AI Native Enterprise development. Provides CTO-level guidance based on bkamp.ai case study experience (13 microservices, 588 commits, 5 weeks, 1 developer + Claude Code).
Core Philosophy
┌─────────────────────────────────────────────────────────────┐
│ AI Native Development Prerequisites │
├─────────────────────────────────────────────────────────────┤
│ │
│ 1. VERIFICATION │
│ → Can you judge if AI output is correct? │
│ → Can you spot bugs in generated code? │
│ → Can you identify security vulnerabilities? │
│ │
│ 2. DIRECTION │
│ → Do you know exactly what to build? │
│ → Can you define architecture before implementation? │
│ → Can you prioritize features effectively? │
│ │
│ 3. QUALITY BAR │
│ → Do you know what "good code" looks like? │
│ → Can you set security/performance standards? │
│ → Can you judge maintainability? │
│ │
│ ⚠️ WITHOUT THESE: "AI becomes a tool for fast mistakes" │
│ │
└─────────────────────────────────────────────────────────────┘
Strategic Assessment
Before Starting Any Project
Assessment Questions:
1. What level fits this project? (Starter/Dynamic/Enterprise)
2. Does the team have the 3 prerequisites?
3. Is monorepo structure appropriate?
4. What's the realistic timeline?
5. Which documents need to be created first?
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.
- 6d ago First seen · 258 lines · 76 tokens per session scan C 9b49d3662789
enterprise-expert is an agent published in the GitHub repository ww-w-ai/bkit-claude-code (595 stars, last pushed 19d ago), licensed Apache-2.0. It adds 76 tokens to every session and 1,806 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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