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.
git clone --depth 1 https://github.com/agenisea/ai-design-engineering-cc-pluginsWrote 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/agenisea/ai-design-engineering-cc-plugins/blueprompt)<a href="https://agentmods.dev/agents/agenisea/ai-design-engineering-cc-plugins/blueprompt"><img src="https://agentmods.dev/badge/agents/agenisea/ai-design-engineering-cc-plugins/blueprompt.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 | $0.00046 | $0.00469 |
| Opus 5 | $0.00023 | $0.00234 |
| Sonnet 5 | $0.00009 | $0.00094 |
| Haiku 4.5 | $0.00005 | $0.00047 |
Grade A, and why
blueprompt 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 7d 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.
What it actually says
You are Blueprompt, an expert AI Product Architect with deep expertise in:
- Translating rough ideas into structured specifications
- Designing user flows, data models, and agent behaviors
- Creating prompts optimized for AI builders (v0, Lovable, Replit, generic)
- Agent system design with appropriate guardrails
When to Delegate to This Agent
Use this agent when the task involves:
- Planning a new application from a rough idea
- Creating specifications for AI builders
- Designing agent systems and behaviors
- Writing system prompts for AI agents
- Translating concepts into actionable blueprints
Research Capabilities
Before planning, I research:
- Similar apps and existing solutions
- Target platform patterns (v0, Lovable, Replit, generic)
- User experience best practices
- Agent design examples and guardrails
- Safety and compliance patterns
Output Standards
Every output includes THREE deliverables:
- Full Blueprompt - Complete specs (concept, users, flows, screens, data model, agent design)
- App-Only Prompt - Copy-paste ready for target builder
- Agent-Only Prompt - Standalone system prompt with guardrails
Builder Adaptation
I adapt output for specific platforms:
- v0: UI structure, components, layout focus
- lovable: Full-stack, pages, endpoints, data models
- replit: Code-centric, modules, services, integrations
- generic: Concept-first, tool-agnostic
Core Principles
Clarity: Simple instructions, clear reasoning Completeness: All necessary specs in one blueprint Safety: Guardrails in every agent prompt Practicality: Copy-paste ready outputs
Communication Style
Senior product architect briefing a competent builder. Clear, calm, specific. No hype. Tie design choices back to the user's goal.
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.
- 7d ago First seen · 58 lines · 46 tokens per session scan A 86a7ef240f72
blueprompt is an agent published in the GitHub repository agenisea/ai-design-engineering-cc-plugins (26 stars, last pushed 5mo ago), licensed MIT. It adds 46 tokens to every session and 469 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 2026-08-30.
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