fixed-view-visual-benchmark

fixed-view-visual-benchmark is a skill for Codex from OutlineDriven/outline-driven-development. It costs 57 tokens per session (824 once invoked), scanned A, original, Apache-2.0.

A repeatable visual test that renders a fixed camera view and scores it against a predefined checklist. It verifies that the saved result reaches the required score.

In plain words
What is it for?
Use it to benchmark a scene or interface render with fixed camera, lighting, resolution, and scoring rules.
Why use it?
It replaces subjective visual checking with comparable results and a clear pass threshold.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to benchmark a scene or interface render with fixed camera, lighting, resolution, and scoring rules.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/outlinedriven/outline-driven-development/fixed-view-visual-benchmark
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 OutlineDriven/outline-driven-development --skill fixed-view-visual-benchmark
Clone the repo
git clone --depth 1 https://github.com/OutlineDriven/outline-driven-development

Made for: Codex.

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 fixed-view-visual-benchmark

README.md
[![agentmods](https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/fixed-view-visual-benchmark/github.svg)](https://agentmods.dev/skills/outlinedriven/outline-driven-development/fixed-view-visual-benchmark)
Your own site
<a href="https://agentmods.dev/skills/outlinedriven/outline-driven-development/fixed-view-visual-benchmark"><img src="https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/fixed-view-visual-benchmark/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.

agentmods 80×15 button for fixed-view-visual-benchmark

Your own site · 80×15
<a href="https://agentmods.dev/skills/outlinedriven/outline-driven-development/fixed-view-visual-benchmark"><img src="https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/fixed-view-visual-benchmark.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 824 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00057 $0.00824
Opus 5 $0.00028 $0.00412
Sonnet 5 $0.00011 $0.00165
Haiku 4.5 $0.00006 $0.00082

Measured 5d ago against content hash 670aaea08e79, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

fixed-view-visual-benchmark 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 5d 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.

.devin/skills/fixed-view-visual-benchmark/SKILL.md · 43 lines

How it starts

The opening of the file, as written. The whole thing — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Fixed-view visual benchmark

Contract

Field Bound contract
Trigger A visual needs repeatable fixed-view rendering and independent rubric scoring.
Authority Reversible local with capture consent: write only named local artifacts; capture consent required before rendering.
Side effect Fixed-view visual benchmark: renders and scores the fixed view against the frozen rubric.
Done The saved render clears the frozen rubric threshold.
Stop Stalled; render blocked; budget exhausted. Bound: fixed view rig, rubric threshold, render budget.

Inputs

  • Fixed view rig (required): camera position and orientation, scene definition, render settings (resolution, samples, lighting, post-processing). All parameters that affect the rendered output must be named and frozen.
  • Frozen rubric threshold (required): the minimum aggregate score that defines a passing render, plus the rubric dimensions and their weights.
  • Render budget (required): the maximum render attempts or time allowed, declared before work begins.

Procedure

  1. Bind the fixed view rig, rubric threshold, and render budget. Freeze all three before any mutation. Done when: the rig, threshold, and budget are named and frozen.
  2. Render the fixed view through a specified rendering interface with reproducibility controls. The interface must accept the frozen rig parameters and produce a deterministic output: same camera, same scene, same settings, same result. Record the interface name, version, and the exact parameter set used. If the interface is non-deterministic (stochastic sampling, temporal effects), declare the seed or averaging strategy that makes repeated renders comparable. Done when: a render is produced from the frozen rig with the interface and parameters recorded.
  3. Score the render against the frozen rubric independently. The rubric defines scoring dimensions (for example: composition, lighting accuracy, material fidelity, geometric correctness), each with a weight summing to 1.0 and a 0–10 scale per dimension. The aggregate score is the weighted sum. Score each dimension against the rubric criteria, not against the previous render. Record per-dimension scores, the aggregate, and the threshold. Done when: the rubric score is recorded with per-dimension breakdown.
  4. Stop at success (aggregate score clears the threshold), any non-success terminal, or the bound. Done when: a terminal class is reached and named.
  5. Persist the run record to .outline/loops/fixed-view-visual-benchmark/<run_id>/ when durable. Emit receipt.json before return. Done when: the receipt is written with the saved render path, per-dimension scores, aggregate, threshold, and terminal class.

Read the full file on GitHub · 43 lines

Files

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.

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. 5d ago First seen · 43 lines · 57 tokens per session scan A 670aaea08e79

Subscribe to this mod's changes

fixed-view-visual-benchmark is a skill published in the GitHub repository OutlineDriven/outline-driven-development (52 stars, last pushed 4d ago), licensed Apache-2.0. It adds 57 tokens to every session and 824 once invoked, about $0.0003 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 2026-09-03.

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