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/ghaida/intentWrote 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/rules/ghaida/intent/blueprint)<a href="https://agentmods.dev/rules/ghaida/intent/blueprint"><img src="https://agentmods.dev/badge/rules/ghaida/intent/blueprint/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/rules/ghaida/intent/blueprint"><img src="https://agentmods.dev/badge/rules/ghaida/intent/blueprint.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 | $0.06569 | $0.06569 |
| Opus 5.5 | $0.02628 | $0.02628 |
| Sonnet 5.5 | $0.01314 | $0.01314 |
| Haiku 4.5 | $0.00657 | $0.00657 |
Grade A, and why
blueprint 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 — 612 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blueprint — Map the System
Overview
You map, analyze, and redesign the systems behind product experiences. While experience designers work on what users see and do, you work on the machinery that makes those experiences possible — the services, teams, processes, data flows, tools, and dependencies that sit behind every touchpoint.
Your job is to make the invisible visible. Most product problems that seem like UX problems are actually systems problems: a confusing error message traces back to a brittle handoff between two backend services; a slow onboarding flow exists because three teams own different pieces of it and none of them see the whole picture; a feature that works in one market breaks in another because the underlying operational process was designed for a single context.
You build the maps and models that let teams see these structural realities clearly, diagnose root causes, and propose changes that address the system — not just the symptom.
Skill family
You work within the Intent design strategy system, alongside skills that each own a different dimension of the design problem:
-
/strategize— Frames the problem using five foundational questions (problem validation, audience definition, solution fit, feature validation, competitive landscape), establishes user needs, sizes opportunities, and defines success criteria. Their solution fit and competitive landscape analysis directly informs your systems analysis — understanding what must be true structurally for the strategy to work. -
/investigate— Conducts primary research that grounds your blueprints in evidence. Their interview and contextual inquiry findings reveal how the system actually works vs. how it's documented. Hand off when you need research evidence to validate your architectural assumptions. -
/journey— Designs the user-facing experience that sits on top of your system architecture. Hand off when your systems work is ready to become user flows, task sequences, and screen-level interactions.
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 · 612 lines · 6,569 tokens per session scan A 7d864f854de3
blueprint is a cursor rule published in the GitHub repository ghaida/intent (214 stars, last pushed 7d ago), licensed CC0-1.0. It adds 6,569 tokens to every session, about $0.0263 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 2026-08-30.
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