Agent Skill to Recursive Decision Ledger
Agent Skill to Recursive Decision Ledger is a verified SKILL blueprint on Promptally in Fullstack & Backend Engineering optimized for leading AI models. Run repeated rollouts ("Prime Gauss" style recursive prompting) while keeping an append-only decision ledger of trials, marks, coherence checks, and promotion gates, so recursive confidence never auto-approves live trading, deploy, or destructive actions. 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. Available to explore, customize with pre-filled variables, and copy with zero authentication required.
Technical Specifications
| Specification | Value |
|---|---|
| Artifact type | SKILL (Fullstack & Backend Engineering) |
| Compatible engines | Universal / Model Agnostic |
| Input variables | None (pre-filled) |
| Approximate tokens | 701 |
| Source file | SKILL.md |
| Access tier | Free public (MIT) |
Pre-Filled Template
---
name: recursive-decision-ledger
description: Run repeated rollouts ("Prime Gauss" style recursive prompting) while keeping an append-only decision ledger of trials, marks, coherence checks, and promotion gates, so recursive confidence never auto-approves live trading, deploy, or destructive actions. 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.
## 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:
- the candidate beats the prior accepted winner on the chosen metric;
- correctness and replay checks pass;
- risk limits are explicit;
- the evidence is durable;
- the user has approved the live step when needed.
## Summary Shape
Lead with the decision, not the drama:
```text
Rollout 15 complete. The prior winner still holds, but edge deteriorated 17%.
Status: watch, not live. Next gate: 20 replay fills with fresh orderbook age
below threshold.
```
How to use this skill
- Review the pre-filled example and source files above.
- Copy the template or download
SKILL.md, then use it in your model, IDE, or workflow tool. - Compare your result with the sample output when one is provided.
Frequently Asked Questions
How do I use Agent Skill to Recursive Decision Ledger?
Open the skill on Promptally, review the pre-filled example, then copy the template or download SKILL.md and paste it into your model, IDE or workflow tool. Agent Skill to Recursive Decision Ledger is a static blueprint with no dynamic variables. Copy it and use it as-is.
Is Agent Skill to Recursive Decision Ledger free?
Yes. Agent Skill to Recursive Decision Ledger is free to view, copy and download on Promptally without creating an account. It is published under the MIT license.
What variables does Agent Skill to Recursive Decision Ledger need?
Agent Skill to Recursive Decision Ledger is a static blueprint with no dynamic variables. Copy it and use it as-is.