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.
npx skills add CheshireJCat/blender --skill multiview-fit-loopgit clone --depth 1 https://github.com/CheshireJCat/blenderWrote 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.
[](https://agentmods.dev/skills/cheshirejcat/blender/multiview-fit-loop)<a href="https://agentmods.dev/skills/cheshirejcat/blender/multiview-fit-loop"><img src="https://agentmods.dev/badge/skills/cheshirejcat/blender/multiview-fit-loop/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cheshirejcat/blender/multiview-fit-loop"><img src="https://agentmods.dev/badge/skills/cheshirejcat/blender/multiview-fit-loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.00554 |
| Opus 5 | $0.00035 | $0.00277 |
| Sonnet 5 | $0.00014 | $0.00111 |
| Haiku 4.5 | $0.00007 | $0.00055 |
Grade A, and why
multiview-fit-loop 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 10d ago.
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.
This is a copy
89% identical to multiview-fit-loop — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multiview Fit Loop
This skill closes the missing loop: render → compare → adjust → render again. It is mandatory when a user says the model still does not fit the templates/originals.
Required loop
- Render flat, material-independent silhouettes for every available template view: front, side, back, top.
- Extract the template object mask, excluding labels, cyan guides, and background.
- Compare template vs render per view:
- bbox center and size
- centroid drift
- silhouette coverage/IoU where modality is valid
- visual overlay
- Convert measured deltas into model/camera/recipe adjustments.
- Rebuild or transform the model.
- Repeat until all hard gates pass or document the remaining conflict.
Constraint inconsistency gate
Before forcing adjustments, check whether the supplied orthographic templates are mutually consistent. A single rigid 3D model cannot simultaneously satisfy contradictory physical ratios, for example if side view says total depth is 0.39 of height but top view says depth is 0.98 of width. When this occurs, stop claiming final fit, write a conflict report, and create separate variants or ask which view is canonical.
Hard gates
- all required views have validation reports and overlays;
- bbox center drift <= 1.5% of image width;
- bbox size drift <= 3% for front, <= 5% for side/top/back first-pass depth;
- structural part count exact;
- texture UV regions still valid after geometry changes.
View mask rule
For annotated wireframes, choose a template mask mode that isolates the intended construction/object lines and excludes guide colors, labels, captions, and background annotations. For Blender validation renders, use a flat white silhouette on black, not beauty renders with glow/context elements.
Scripts
scripts/multiview_fit_report.pycompares view pairs and writes JSON + overlays.
Adjustment rule
Prefer changing recipe parameters or source geometry over camera scale tricks. Camera scale may be used only after model dimensions are correct.
What ships with it
1 file 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.
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.
- 10d ago First seen · 48 lines · 70 tokens per session scan A d4d79dfecdc7
multiview-fit-loop is a skill published in the GitHub repository CheshireJCat/blender (26 stars, last pushed 20d ago), licensed MIT. It adds 70 tokens to every session and 554 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to multiview-fit-loop, differing in 2 lines, and is treated as a copy.
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