RE

recursive-decision-ledger

Tracks systematic decision-making and search rollouts, keeping a visible audit trail of trials, winners, and logic for reproducibility.

Install

mkdir -p .claude/skills/recursive-decision-ledger && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/15351" && unzip -o skill.zip -d .claude/skills/recursive-decision-ledger && rm skill.zip

Installs to .claude/skills/recursive-decision-ledger

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

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.
223 chars✓ has a “when” trigger
Advanced

Key capabilities

  • Record rollout IDs and timestamps
  • Capture fresh information ingested
  • Track search space size and model heuristics
  • Mark candidates as accept, watch, reject, decay watch, or needs replay
  • Compare winners against prior winners
  • Append artifacts before summarizing

How it works

This skill records detailed information for each rollout in a ledger, including fresh data, search parameters, candidate marks, and coherence checks, to manage recursive decision processes.

Inputs & outputs

You give it
a request for repeated rollouts or high-dimensional search
You get back
a structured ledger entry and a summary of the decision process

When to use recursive-decision-ledger

  • Running repeated search rollouts
  • Managing recursive optimization tasks
  • Tracking ensemble decisions

About this skill

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:

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:

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.

When not to use it

  • When the user is not asking for repeated rollouts or high-dimensional search
  • When the goal is to prove certainty through recursive prompting
  • When the task does not require a visible evidence trail

Limitations

  • The skill requires recording specific ledger contract items for each rollout
  • The skill does not approve live actions based on recursive confidence alone
  • The skill focuses on managing decision processes, not executing them

How it compares

This skill formalizes recursive decision-making with a structured ledger and explicit coherence marks, providing an auditable trail that differs from informal iterative processes.

Compared to similar skills

recursive-decision-ledger side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
recursive-decision-ledger (this skill)02moNo flagsAdvanced
docetl22moReviewIntermediate
slm-lab-benchmark15moReviewAdvanced
document-classification02moNo flagsIntermediate

Try saying

Example prompts that trigger this skill in your AI assistant.

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