quality-refinement-autoloop

quality-refinement-autoloop is a skill for Claude Code from RobLe3/cc-blender-skill. It costs 83 tokens per session (1,032 once invoked), scanned A, original, MIT.

A self-review process for Blender work that preserves a failed result, identifies what went wrong, and improves the workflow before another attempt.

In plain words
What is it for?
Use it when a result is wrong, unattractive, misaligned, untextured, unanimated, or fails validation or export checks.
Why use it?
It replaces blind tweaking with evidence-based diagnosis. It helps distinguish problems with shape, texture, lighting, animation, export, or the handoff between steps.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it when a result is wrong, unattractive, misaligned, untextured, unanimated, or fails validation or export checks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/roble3/cc-blender-skill/quality-refinement-autoloop
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add RobLe3/cc-blender-skill --skill quality-refinement-autoloop
Clone the repo
git clone --depth 1 https://github.com/RobLe3/cc-blender-skill

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for quality-refinement-autoloop

README.md
[![agentmods](https://agentmods.dev/badge/skills/roble3/cc-blender-skill/quality-refinement-autoloop.svg)](https://agentmods.dev/skills/roble3/cc-blender-skill/quality-refinement-autoloop)
Your own site
<a href="https://agentmods.dev/skills/roble3/cc-blender-skill/quality-refinement-autoloop"><img src="https://agentmods.dev/badge/skills/roble3/cc-blender-skill/quality-refinement-autoloop.svg" alt="Measured on agentmods" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,032 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00083 $0.01032
Opus 5 $0.00042 $0.00516
Sonnet 5 $0.00017 $0.00206
Haiku 4.5 $0.00008 $0.00103

Measured 7d ago against content hash 3f9ba8977f25, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

quality-refinement-autoloop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/ralph_autoloop_plan.py, scripts/release_readiness_check.py, scripts/sanitize_skill_contributions.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugin/skills/quality-refinement-autoloop/SKILL.md · 118 lines

How it starts

The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Quality Refinement Autoloop

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.

Read the full file on GitHub · 118 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 118 lines · 83 tokens per session scan A 3f9ba8977f25

Subscribe to this mod's changes

quality-refinement-autoloop is a skill published in the GitHub repository RobLe3/cc-blender-skill (53 stars, last pushed 4mo ago), licensed MIT. It adds 83 tokens to every session and 1,032 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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