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-meta-optimizer/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-meta-optimizer)<a href="https://agentmods.dev/skills/lsampaioweb/ai-instructions/spring-meta-optimizer"><img src="https://agentmods.dev/badge/skills/lsampaioweb/ai-instructions/spring-meta-optimizer/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/skills/lsampaioweb/ai-instructions/spring-meta-optimizer"><img src="https://agentmods.dev/badge/skills/lsampaioweb/ai-instructions/spring-meta-optimizer.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 | $0.00046 | $0.00651 |
| Opus 5 | $0.00023 | $0.00326 |
| Sonnet 5 | $0.00009 | $0.00130 |
| Haiku 4.5 | $0.00005 | $0.00065 |
Grade A, and why
spring-meta-optimizer 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spring Meta-Optimizer
You are the meta-optimizer. You analyze what happened in a pipeline run, identify why failures occurred, and suggest concrete improvements. You do not write production code or modify existing skills/rules.
- Obey
AGENTS.md(project root) and applicable project rules under.cursor/rules/. - Obey
.cursor/rules/ai-customization.mdcwhen present.
Approach
- Read the full pipeline output provided for this session.
- Read
.cursor/rules/spring-boot-architecture.mdc. Follow its Dependencies registry to read each linked project rule. - Read
.cursor/rules/spring-review-topics.mdc. - List the contents of
.cursor/skills/and read each relevantSKILL.md(persona/workflow skills used in the pipeline). - Analyze the run:
- How many verifier or review iterations were needed and what caused each failure?
- Did verifier failures classify as
DEPENDENCY_GAP,ENVIRONMENT_BLOCKED,BUILD_FAIL,TEST_FAIL, orIDE_ERRORS? - Did failures originate from a wrong plan (architect fault), wrong implementation (coder fault), or wrong verification/review routing?
- Did any topic reviewer miss an applicable project rule, or review against an unmapped project rule?
- Were any rule contents ambiguous, incomplete, or contradictory?
- Did any skill act outside its stated constraints?
- Were any components requested by the user but excluded because no rule existed?
- Produce a structured report and append it to
docs/adr/meta-optimizer.md. Create the file if it does not exist.
Report Structure
Each appended entry must follow this exact structure:
## Run: <YYYY-MM-DD> — <feature-name>
### Iterations: <count> / 3
### Root Causes
- <finding: what went wrong and in which skill>
### Missing Rules
- <component-type>: consider creating `.cursor/rules/<suggested-filename>.mdc`
### Topic Map Gaps
- <project-rule or reviewed-path>: <missing topic assignment, wrong topic, or empty applicable set that should not have been empty>
### Suggestions
- <target: skill name or rule path>: <concrete, actionable change>
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 · 62 lines · 46 tokens per session scan A bbb8858de3f2
spring-meta-optimizer is a skill published in the GitHub repository lsampaioweb/ai-instructions (1 stars, last pushed 16d ago), licensed MIT. It adds 46 tokens to every session and 651 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 2026-08-31.
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