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/aidesignblueprint/integrationsWrote 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/aidesignblueprint/integrations/blueprint-doctrine)<a href="https://agentmods.dev/rules/aidesignblueprint/integrations/blueprint-doctrine"><img src="https://agentmods.dev/badge/rules/aidesignblueprint/integrations/blueprint-doctrine/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/aidesignblueprint/integrations/blueprint-doctrine"><img src="https://agentmods.dev/badge/rules/aidesignblueprint/integrations/blueprint-doctrine.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 | $0.00037 | $0.00870 |
| Opus 5.5 | $0.00015 | $0.00348 |
| Sonnet 5.5 | $0.00007 | $0.00174 |
| Haiku 4.5 | $0.00004 | $0.00087 |
Grade A, and why
blueprint-doctrine 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 17d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Design Blueprint
Use these rules when generating agentic product or workflow code.
Validator trio (Pro/Teams, via the AIDB MCP server in .cursor/mcp.json)
spec.validate: score a WRITTEN spec against the 8 spec-quality laws before anyone builds from it (PM lens).architect.validate: score agentic code against the 10 principles below (Engineer lens).design.validate: score a rendered surface against the 8 experience-design laws (Designer lens).
1. Design for delegation rather than direct manipulation
- Slug:
design-for-delegation-rather-than-direct-manipulation - Cluster:
delegation - Guidance: Design experiences around the assignment of work, the expression of intent, the setting of constraints, and the review of results, rather than requiring users to execute each step manually.
2. Ensure that background work remains perceptible
- Slug:
ensure-that-background-work-remains-perceptible - Cluster:
visibility - Guidance: When the system is operating asynchronously or outside the user’s immediate focus, it should provide persistent and proportionate signals that work is continuing.
3. Align feedback with the user’s level of attention
- Slug:
align-feedback-with-the-user-s-level-of-attention - Cluster:
visibility - Guidance: The system should calibrate the depth and frequency of feedback according to whether the user is actively engaged, passively monitoring, or temporarily absent.
4. Apply progressive disclosure to system agency
- Slug:
apply-progressive-disclosure-to-system-agency - Cluster:
trust - Guidance: Provide the minimum information necessary by default, while enabling users to inspect additional detail when confidence, understanding, or intervention is required.
5. Replace implied magic with clear mental models
- Slug:
replace-implied-magic-with-clear-mental-models - Cluster:
delegation - Guidance: The product should help users understand what the system can do, what it is currently doing, what it cannot do, and what conditions govern its behaviour.
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.
- 17d ago Changed 336ba8189ff3
- 18d ago Changed 012468390003
- 19d ago Changed 172e64da0c89
- 23d ago Changed 72b529d750a9
- 26d ago Changed 637d3a4b2e05
- 1mo ago Changed d2095e4ff225
- 1mo ago Changed 7ab96fceb060
- 1mo ago Changed 46695817fc8d
- 2mo ago First seen · 67 lines · 37 tokens per session scan A a88923fd81ff
blueprint-doctrine is a cursor rule published in the GitHub repository aidesignblueprint/integrations (3 stars, last pushed 18d ago), licensed MIT. It adds 37 tokens to every session and 870 once invoked, about $0.0001 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 cursor rules, from other repositories
changelog
Update CHANGELOG.md for user-visible changes (Keep a Changelog).
ai-safe2-sovereign
AI SAFE2 v3.1 Sovereign Security Rules for Cursor.
auto-update-readme
Auto-update README.md when rules are added or modified.
cursor_template
Enforcing engineering standards and governance in AI-First development through automated guardrails.
titanclip-monorepo
TitanClip pnpm monorepo layout, scripts, and scoping.
ponytail
Ponytail, lazy senior dev mode. Always pick the simplest solution that works.