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.
npx skills add andregusman-raiz/a-gusman-claude --skill ag-referencia-anti-ciclo-preditivogit clone --depth 1 https://github.com/andregusman-raiz/a-gusman-claudeWrote 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/andregusman-raiz/a-gusman-claude/ag-referencia-anti-ciclo-preditivo)<a href="https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-referencia-anti-ciclo-preditivo"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-referencia-anti-ciclo-preditivo/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/andregusman-raiz/a-gusman-claude/ag-referencia-anti-ciclo-preditivo"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-referencia-anti-ciclo-preditivo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00042 | $0.09530 |
| Opus 5 | $0.00021 | $0.04765 |
| Sonnet 5 | $0.00008 | $0.01906 |
| Haiku 4.5 | $0.00004 | $0.00953 |
Grade A, and why
ag-referencia-anti-ciclo-preditivo 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 9d 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 — 741 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Anti-Ciclo Preditivo — Regras Universais
30 regras derivadas de diagnostico pos-mortem de um sistema preditivo que consumiu 6 meses e 13 iteracoes sem confirmar sinal preditivo. Custo de descobrir cada regra = ~2 semanas de ciclo real. Aplicaveis a qualquer projeto: churn, inadimplencia, fraud, forecasting, scoring, anomaly, recommendation.
Escopo: compoe com ~/Claude/CLAUDE.md (workspace) e CLAUDE.md local do projeto.
Quando carregar: inicio de qualquer projeto preditivo, antes de treinar modelo, antes de declarar "sinal detectado", antes de deploy de pipeline preditivo.
Navegacao
- I — Epistemologia (M1-M10)
- II — Arquitetura (M11-M15)
- III — Decisao (R1-R3)
- IV — Data Coverage (DC1-DC3)
- V — Multi-segmento (S1-S3)
- VI — Particoes/Populacoes (P1-P3)
- VII — Metodologia (M16-M18)
- VIII — Ground-truth (G1-G3)
- IX — Adversariais (A1-A3)
- X — Meta-regra de composicao (tiers + 5 criticas)
- Apendice A — Mapa sintoma → regra
- Apendice B — Enforcement roadmap
- Apendice C — Aplicacao em projetos Raiz
Vocabulario agnostico
| Termo | Significado |
|---|---|
| Sinal preditivo | Lift estatisticamente significativo de um modelo/estrategia sobre baseline trivial |
| Ground-truth observavel | Valor real do target, acessivel apenas apos o instante de decisao T-0 |
| Baseline forte | Modelo simples (regressao linear, heuristica de negocio, regra de ouro) + fonte de referencia externa confiavel |
| Walkforward / OOT | Validacao temporal onde treino usa apenas dados =T |
| Kill-criterion | Criterio pre-registrado de abandono do projeto (threshold + amostra minima + CI) |
| Null test | Teste com labels embaralhadas / assignment aleatorio para calibrar noise floor |
| Noise floor | Magnitude de efeito produzida sob hipotese nula (zero sinal) por artefato matematico |
| Metrica primaria | Metrica que define sucesso do projeto (ROI, F1, recall@K, precision, AUC, Brier, log-loss, etc) |
| Metrica de calibracao | Metrica que mede "quao bem-calibradas sao as probabilidades" (Brier, log-loss, ECE, reliability) |
| Ciclo N | N-esima iteracao de "vou melhorar o sistema"; ciclos tipicos sao 2-4 semanas cada |
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.
- 9d ago First seen · 741 lines · 42 tokens per session scan A 598d84079fa4
ag-referencia-anti-ciclo-preditivo is a skill published in the GitHub repository andregusman-raiz/a-gusman-claude (19 stars, last pushed 3d ago), licensed MIT. It adds 42 tokens to every session and 9,530 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 2026-09-03.
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