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Recursive Decision Ledger

ASecurity

Use when the user asks for repeated rollouts, marked decision processes, high-dimensional search, stochastic optimization, local-optima exploration, ensemble comparison, or recursive reasoning with a visible evidence trail.

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  • Added September 19, 2026
ai-agentsbashapi

Works with

  • api

Security analysis

A100/100

Scanned September 19, 2026

npx -y skills add majinmagros/magros.ai-skills --skill recursive-decision-ledger --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: recursive-decision-ledger
description: Use when the user asks for repeated rollouts, marked decision processes, high-dimensional search, stochastic optimization, local-optima exploration, ensemble comparison, or recursive reasoning with a visible evidence trail.
license: MIT
metadata:
  origin: ECC
tools: Read, Write, Edit, Bash, Grep, Glob
---

# Recursive Decision Ledger

Use this skill when the user is trying to force deeper computation through
repeated rollouts or "Prime Gauss" style recursive prompting. Preserve the useful
part: repeated trials, prior memory, fresh information, and explicit marks.
Remove the unsafe part: pretending the loop proves certainty.

## Quando usar

- "roda N vezes e decide", "busca recursiva com trilha de evidência"
- Otimização estocástica, ensemble, exploração de ótimos locais
- Decisão repetida que precisa de ledger (accept/watch/reject) + promotion gate
- Não use para: loop simples sem decisão (isso é continuous-agent-loop); rodada única

## Ledger Contract

Every rollout should record:

- rollout id and timestamp;
- prior accepted winner and prior watchlist;
- fresh information ingested;
- search space size;
- model families or heuristics used;
- trial count and effective trial count;
- top candidates;
- decision marks;
- coherence marks against the prior ledger;
- promotion gate result.

Prefer JSONL for append-only ledgers and Markdown for human summaries.

## Rollout Loop

1. Load the prior ledger.
2. Capture new information at time-step zero.
3. Run the bounded search.
4. Mark each candidate: accept, watch, reject, decay watch, or needs replay.
5. Compare winners against prior winners and latest marked rollout.
6. Downgrade candidates when drift, tail risk, stale data, or failed replay
   invalidates the previous mark.
7. Append artifacts before summarizing.

## Coherence Mark

Include a compact coherence mark:

```text
Ensemble matches prior winner: true
Recursive matches prior winner: false
Latest rollout match: true
Live promotion allowed: false
Reason: replay and freshness gates not satisfied
```

## Promotion Rules

For trading, capital allocation, production deploys, migrations, or destructive
ops, recursive confidence is not approval.

Default to paper, dry-run, read-only, preview, or staged mode unless the user
explicitly approves the live action and the repo/service gate supports it.

Promote only when:

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