# Modeler Decision Logger

Faithfully append a human modeler's choice and rationale to one canonical...

- Repository: https://github.com/zhnnky329/MathModeling-skills (1073 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-09-24
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add zhnnky329/MathModeling-skills --skill modeler-decision-logger -g -a claude-code -y`
Codex: `npx skills add zhnnky329/MathModeling-skills --skill modeler-decision-logger -g -a codex -y`
Cursor: `npx skills add zhnnky329/MathModeling-skills --skill modeler-decision-logger -g -a cursor -y`
Gemini CLI: `npx skills add zhnnky329/MathModeling-skills --skill modeler-decision-logger -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add zhnnky329/MathModeling-skills`

## Description

Faithfully append a human modeler's choice and rationale to one canonical per-subquestion JSONL decision ledger. Use after a choice card is answered or when migrating legacy decision artifacts; never originate or improve the decision.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Purpose

Make human judgment traceable without multiplying decision files.

# Canonical Output

`methods/Qx/qx_decisions.jsonl`

One JSON object per line. Records are append-only.

Use `planning/framing_decisions.jsonl` for global/pre-Qx framing decisions.

# Required Fields

```json
{
  "schema_version": 1,
  "decision_id": "q1_method_choice",
  "decision_type": "method_choice",
  "status": "DECIDED",
  "decided_by": "human",
  "captured_in_mode": "learning",
  "choice": "M2",
  "rationale": "Human-authored reason tied to evidence.",
  "evidence_refs": ["methods/Q1/probes/risk_probe_summary.json"],
  "decided_at": "ISO-8601",
  "supersedes": null
}
```

Optional structured fields may include confidence, rejected alternatives, round action, claim scope, assumption labels, or fallback activation.

# Workflow

1. Receive the human's answer, the choice-card ID, and evidence paths.
2. Preserve the user's meaning and wording. Normalize only structure, identifiers, and whitespace.
3. Verify:
   - the choice is one of the presented options or explicitly records a user-supplied alternative;
   - evidence paths exist;
   - rationale is non-empty and contains no placeholder;
   - the record does not falsely label AI-authored prose as human-authored.
4. Append one JSON line.
5. If revising a decision, append a new record with `supersedes`; never overwrite history.
6. Update the compact history in `qx_method_card.md` only when the decision changes method state.
7. Update the manifest gate/status fields when present.

# Decision Types

Typical values:

- `framing`
- `method_choice`
- `fallback_activation`
- `result_verdict`
- `stability_verdict`
- `assumption_necessity`
- `claim_scope`
- `package_signoff`
- `submission_authorization`

# Staleness

Mark a decision stale only when its cited evidence materially changed:

The rest: https://github.com/zhnnky329/MathModeling-skills/blob/HEAD/.claude/skills/modeler-decision-logger/SKILL.md