deepen-architecture

deepen-architecture is a cursor rule for Cursor from danielvm-git/bigpowers. It costs 67 tokens per session (3,549 once invoked), scanned A, original, MIT.

Find deepening opportunities in a codebase, informed by the domain language in specs/tech-architecture/tech-stack.md and the decisions in specs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/danielvm-git/bigpowers/deepen-architecture
Clone the repo
git clone --depth 1 https://github.com/danielvm-git/bigpowers

Made for: Cursor.

Wrote 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.

agentmods badge for deepen-architecture

README.md
[![agentmods](https://agentmods.dev/badge/rules/danielvm-git/bigpowers/deepen-architecture.svg)](https://agentmods.dev/rules/danielvm-git/bigpowers/deepen-architecture)
Your own site
<a href="https://agentmods.dev/rules/danielvm-git/bigpowers/deepen-architecture"><img src="https://agentmods.dev/badge/rules/danielvm-git/bigpowers/deepen-architecture.svg" alt="Measured on agentmods" height="20"></a>
Per session 67 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,549 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00067 $0.03549
Opus 5 $0.00034 $0.01775
Sonnet 5 $0.00013 $0.00710
Haiku 4.5 $0.00007 $0.00355

Measured today against content hash 35ff8575e0ce, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deepen-architecture 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 today.

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.

.cursor/rules/deepen-architecture.mdc · 260 lines

How it starts

The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deepen Architecture

Surface architectural friction and propose deepening opportunities — refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.

Distinct from define-language and model-domain: Use this skill to find module-level refactoring opportunities in the codebase. Use define-language to produce a canonical glossary of terms. Use model-domain to stress-test a plan through a domain-model interview.

HARD GATE — Deep modules must solve a forcing function, not just be "nice abstractions." If you cannot articulate why the abstraction exists, it is premature.

Glossary

Use these terms exactly in every suggestion. Consistent language is the point — don't drift into "component," "service," "API," or "boundary." Full definitions in LANGUAGE.md.

  • Module — anything with an interface and an implementation (function, class, package, slice).
  • Interface — everything a caller must know to use the module: types, invariants, error modes, ordering, config. Not just the type signature.
  • Implementation — the code inside.
  • Depth — leverage at the interface: a lot of behaviour behind a small interface. Deep = high leverage. Shallow = interface nearly as complex as the implementation.
  • Seam — where an interface lives; a place behaviour can be altered without editing in place. (Use this, not "boundary.")
  • Adapter — a concrete thing satisfying an interface at a seam.
  • Leverage — what callers get from depth.
  • Locality — what maintainers get from depth: change, bugs, knowledge concentrated in one place.

Key principles (see LANGUAGE.md for the full list):

  • Deletion test: imagine deleting the module. If complexity vanishes, it was a pass-through. If complexity reappears across N callers, it was earning its keep.
  • The interface is the test surface.
  • One adapter = hypothetical seam. Two adapters = real seam.

This skill is informed by the project's domain model — specs/tech-architecture/tech-stack.md and any specs/adr/. The domain language gives names to good seams; ADRs record decisions the skill should not re-litigate. See CONTEXT-FORMAT.md and ADR-FORMAT.md.

Read the full file on GitHub · 260 lines

Changes

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.

  1. today First seen · 260 lines · 67 tokens per session scan A 35ff8575e0ce

Subscribe to this mod's changes

deepen-architecture is a cursor rule published in the GitHub repository danielvm-git/bigpowers (162 stars, last pushed 2d ago), licensed MIT. It adds 67 tokens to every session and 3,549 once invoked, about $0.0003 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 2026-09-03.