Quality Refinement Autoloop
SkillDev toolsRun a self-refinement loop when a Blender result is subpar, user expectations are not met, validation fails, or repeated issues reveal missing skill depth. The loop diagnoses the gap, decides whether to repair the artifact or acquire/refine a generic skill, sanitizes lessons for reusable publication, updates docs/versioning, validates, and prepares stage/commit/push when explicitly requested.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Quality Refinement Autoloop skill
What this skill tells your AI
The instructions your AI receives, as published by cheshirejcat/blender in skills/create-3d-model/references/modules/quality-refinement-autoloop/SKILL.md and read by ahel’s review.
Use this when the user says the result is wrong, ugly, not aligned, not textured, not animated, not exportable, or otherwise below expectation. The goal is not to keep tweaking blindly. The goal is to convert failure into a reusable, generic skill improvement before trying again.
Autoloop phases
0. Freeze and preserve
- Stop making product changes immediately.
- Preserve the last accepted baseline and the failed artifact.
- Name the failed branch/version honestly; do not overwrite accepted outputs.
1. Evidence capture
Collect the smallest evidence set that proves the failure:
- user feedback quote or summary;
- source/reference files used;
- current output path/version;
- relevant render/contact sheet/overlay/audit report;
- scene/material/object inventory if the failure is inside Blender.
2. Diagnose failure dimension
Classify the primary gap:
- geometry / silhouette / landmarks;
- multiview/depth consistency;
- UV / atlas / texture fit;
- closed surface coverage (front/back/side);
- look/material/lighting calibration;
- animation/motion/export truth;
- orchestration/handoff between skills;
- missing validator or missing deterministic helper script.
3. Skill-gap decision
Ask: does the current skill stack already contain a generic method for this failure?
- If yes: run the existing skill and repair the artifact.
- If no: add/refine a generic skill first, then repair.
- If repeated failures come from skill interplay, update the harmonizer/handoff rule, not just a leaf skill.
4. Sanitize the lesson
Before writing a skill change:
- remove project/client/asset names;
- remove secrets, raw logs, private paths, personal data, and copyrighted source content;
- keep only reusable method, gates, scripts, and failure patterns;
- describe inputs/outputs generically;
- prefer deterministic scripts for fragile audits.
5. Patch skill stack
Apply the smallest publishable change:
- one concise skill or one concise section in an existing skill;
- optional helper script if the validation is repeatable;
- harmonizer update if ordering/handoff changed;
- manifest entry/version update.
6. Validate skill change
Required checks:
- scripts compile;
- manifest paths exist;
- skill graph audit passes with harmonizer present;
- sanitizer scan passes for project-specific terms;
- if applicable, run the new helper against the failed artifact and save a report.
7. Repair product only after skill gate
Rebuild or repair from the correct baseline using the improved skill. Do not reuse rejected outputs unless explicitly marked as source evidence.
8. Release prep when requested
Only when the user asks to publish/commit/push:
- fetch latest remote and confirm local branch is up to date;
- resolve/harmonize conflicts before staging;
- bump version using semver appropriate to scope;
- update the package
SKILL.md,manifest.json, provenance, UI metadata, and release notes in the owning repository when relevant; - run sanitizer and compile/audit checks;
- stage, commit, and push using the configured remote.
Hard rules
- Do not bake task-specific examples into public skills.
- Do not call overlay curves/planes “texture coverage” unless the real mesh surface also passes coverage gates.
- Do not tune lighting/materials to hide geometry or UV failures.
- Do not claim export support if the effect exists only in Blender Python or a render sequence.
- Do not push without an explicit user request and an up-to-date remote check.
Recommended artifacts
Save these near the project output when running the loop:
RALPH_OR_QUALITY_LOOP_REPORT.mdfailure_evidence/or references to existing renders/reportsskill_gap_decision.jsonsanitization_report.jsonvalidation_report.json
Scripts
scripts/ralph_autoloop_plan.pycreates a generic failure-classification and loop plan from feedback/artifact hints.scripts/sanitize_skill_contributions.pyscans skill files for project-specific or private terms before publication.scripts/release_readiness_check.pyperforms lightweight Pi-package manifest, module-path, metadata, license, and connector checks before commit/push; it also retains compatibility with the original upstream repository layout.
Signals
- GitHub stars
- 26
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
quality-refinement-autoloop- Source
- github.com/cheshirejcat/blender