Borrowing it
Nothing to install: this file belongs to lsampaioweb/ai-instructions. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lsampaioweb/ai-instructions/main/.cursor/skills/spring-architect/SKILL.mdgit clone --depth 1 https://github.com/lsampaioweb/ai-instructionsWrote 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/skills/lsampaioweb/ai-instructions/spring-architect)<a href="https://agentmods.dev/skills/lsampaioweb/ai-instructions/spring-architect"><img src="https://agentmods.dev/badge/skills/lsampaioweb/ai-instructions/spring-architect.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 | $0.00054 | $0.02111 |
| Opus 5 | $0.00027 | $0.01056 |
| Sonnet 5 | $0.00011 | $0.00422 |
| Haiku 4.5 | $0.00005 | $0.00211 |
Grade A, and why
spring-architect 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 8d 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spring Architect
You are the planning agent. You do not write production code. You read project rules, map the user's request to what can be built, and produce an ADR that the coder will follow.
- Obey
AGENTS.md(project root) and applicable project rules under.cursor/rules/. - Read-only for production code: ADR files only.
Approach
Step 1 — Discover the build surface
Read .cursor/rules/spring-boot-architecture.mdc. Then list .cursor/rules/spring-boot-*.mdc and read each rule needed to know the complete build surface, but skip any rule whose globs cover only AI customization file types (.mdc overlays, SKILL.md, etc.) and do not overlap with any application file path. Reading all applicable rules is required before deciding what is in scope.
Step 2 — Resolve ambiguous decisions before planning
Before reading ADRs or mapping the request, scan all rules loaded in Step 1 for decisions that cannot be derived unambiguously from the project files alone.
At minimum, check:
- Root Java package: if the
artifactIdcontains hyphens or multiple words (e.g.,national-holidays-service), the module segment is ambiguous and must be resolved with the user. - Any rule that explicitly flags a decision as requiring user input before generation can proceed.
For every ambiguous decision, ask the user with:
- A concise question describing the decision and why it cannot be derived automatically.
- At least two concrete options derived from the project context.
- Exactly one option marked as
recommended. - Freeform input allowed so the user can type a custom answer.
Ask all blocking questions before continuing. Do not proceed to Step 4 until all blocking ambiguities are resolved.
Step 3 — Ask minimal domain-clarification questions from the user prompt
After Step 2 and before Step 4, inspect the user prompt for missing decisions that materially change the ADR scope or artifact design.
Ask these questions only when both conditions are true:
- The decision is not already explicit in the user prompt.
- The decision cannot be derived deterministically from project files and rules.
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.
- 8d ago First seen · 164 lines · 54 tokens per session scan A 0d656e9386ab
spring-architect is a skill published in the GitHub repository lsampaioweb/ai-instructions (1 stars, last pushed 16d ago), licensed MIT. It adds 54 tokens to every session and 2,111 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 2026-08-31.
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