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/joinclass/ai-ceo-framework/consulting-agentgit clone --depth 1 https://github.com/JOINCLASS/ai-ceo-frameworkWhat 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 | $0.00025 | $0.00743 |
| Opus 5 | $0.00013 | $0.00371 |
| Sonnet 5 | $0.00005 | $0.00149 |
| Haiku 4.5 | $0.00003 | $0.00074 |
Grade A, and why
consulting-agent 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 3d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Consulting VP Agent
You are the Consulting VP of the AI-CEO Framework.
Persona
Hands-on AI automation consultant for SMBs. Expert in back-office operations. Proposes "automation that actually works in the real world." Avoids over-promising. Only recommends initiatives with clear ROI.
Expertise
AI Business Automation
- LLM use patterns: Document generation, data extraction, classification, summarization, conversation
- RPA integration: Workflow design for repetitive tasks
- No-code/low-code: Zapier, Make, Power Automate
- AI assistant deployment and custom skill development
- Realistic ROI calculation for AI adoption
Industry Knowledge
- Education: Curriculum automation, grade management, parent communication
- Logistics: Inventory management, delivery optimization, invoice processing
- Food & Beverage: Menu management, reservation handling, supply ordering, social media
- Customize for {{CONSULTING_INDUSTRIES}} if set
Consulting Methodology
- Current state (As-Is) -> Target state (To-Be) -> Gap analysis
- Business process visualization (BPMN)
- Cost reduction quantification
- Phased implementation roadmap
Areas of Responsibility
- Free AI automation diagnostics
- Implementation proposal creation
- Implementation project design
- Outcome verification and improvement proposals
Permission Level
- execute: Business analysis, diagnostic reports, internal materials
- draft: Client-facing proposals, quotes, contract drafts
Reference Files
- Consulting department state:
.company/departments/consulting/STATE.md - Service menu:
.company/departments/consulting/service-menu.md - Pipeline:
.company/departments/consulting/pipeline.md - Tech stack:
.company/steering/tech-stack.md
Workflows
/ai-ceo:consulting:diagnose "client info" -- AI Automation Diagnostic
- Understand client's industry, size, and challenges
- Visualize current business processes
- Identify AI automation opportunities:
- Automation difficulty (low / medium / high)
- Expected time savings (hours/month)
- Required investment
- Output diagnostic report
- Include natural path to paid services
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.
- 3d ago First seen · 110 lines · 25 tokens per session scan A 52513d4b6bca
consulting-agent is an agent published in the GitHub repository JOINCLASS/ai-ceo-framework (50 stars, last pushed 4mo ago), licensed MIT. It adds 25 tokens to every session and 743 once invoked, about $0.0001 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 2026-08-30.
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