Best fit
- 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 tr…
affaan-m/ECC
recursive-decision-ledger
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.
71Collecting
See how to use itView GitHub source
npx skills add https://github.com/affaan-m/ECC --skill "skills/recursive-decision-ledger"Automated source guideGeneral workflowStandard source
Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
Source-grounded usage guide: 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 pr…
npx skills add https://github.com/affaan-m/ECC --skill "skills/recursive-decision-ledger"The pinned source supports a structured brief, but not an expanded tutorial. Only detected inputs, outputs, and sections are shown.
311 source words · 5 usable sections
Source workflow
Read recursive-decision-ledger through these 4 source sections
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
Ledger Contract
Every rollout should record:
rollout id and timestamp;prior accepted winner and prior watchlist;fresh information ingested;
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,…
Load the prior ledger.Capture new information at time-step zero.Run the bounded search.
Coherence Mark
Include a compact coherence mark:
Include a compact coherence mark:
Promotion Rules
For trading, capital allocation, production deploys, migrations, or destructive ops, recursive confidence is not approval.
the candidate beats the prior accepted winner on the chosen metric;correctness and replay checks pass;risk limits are explicit;
Source checklist
Verify each item before delivery
The source section “Ledger Contract” has been checked.
The source section “Rollout Loop” has been checked.
The source section “Coherence Mark” has been checked.
The source section “Promotion Rules” has been checked.
FAQ
What does the recursive-decision-ledger source document cover?
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 pr…
How do I install recursive-decision-ledger?
The source record exposes this install command: npx skills add https://github.com/affaan-m/ECC --skill "skills/recursive-decision-ledger". Inspect the command and pinned source before running it.
Repository stars
234,327
Repository forks
35,711
Quality
71/100
Source repository last pushed
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Documentation24/30
Specificity15/25
Maintenance20/20
Trust signals12/25
View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 2 min
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
- Load the prior ledger.
- Capture new information at time-step zero.
- Run the bounded search.
- Mark each candidate: accept, watch, reject, decay watch, or needs replay.
- Compare winners against prior winners and latest marked rollout.
- Downgrade candidates when drift, tail risk, stale data, or failed replay invalidates the previous mark.
- 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.
- Source repo
- affaan-m/ECC
- Skill path
- skills/recursive-decision-ledger/SKILL.md
- Commit SHA
- 4e973d3eaf92
- Repository license
- MIT
- Data collected