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 kwakseongjae/oh-my-design --skill bench-fixture-gengit clone --depth 1 https://github.com/kwakseongjae/oh-my-designWrote 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/kwakseongjae/oh-my-design/bench-fixture-gen)<a href="https://agentmods.dev/skills/kwakseongjae/oh-my-design/bench-fixture-gen"><img src="https://agentmods.dev/badge/skills/kwakseongjae/oh-my-design/bench-fixture-gen/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/kwakseongjae/oh-my-design/bench-fixture-gen"><img src="https://agentmods.dev/badge/skills/kwakseongjae/oh-my-design/bench-fixture-gen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.00429 |
| Opus 5.5 | $0.00000 | $0.00172 |
| Sonnet 5.5 | $0.00000 | $0.00086 |
| Haiku 4.5 | $0.00000 | $0.00043 |
Grade A, and why
bench-fixture-gen 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 1mo 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.
What it actually says
bench-fixture-gen (benchmark-internal, NOT a user skill)
Generates the shared per-task fixture that every competing arm starts from: a realistic dataset plus an image asset base. Fairness rule: fixtures are generated ONCE per task by this preprocessor and sealed (sha256) before any arm runs; arms never generate their own.
Workflow
- Author a fixture spec (
fixture-spec.json):task_iddataset: {global_key(window global),entities: [{ name, count, fields: [{name, kind, enum?, range?}], relations? }],disclosure}images: generate-task-assets item list ({file, prompt, style})
- Dataset:
node scripts/generate-task-dataset.mjs --spec <spec> --out <dir>- grok-4.6 authors realistic records for the spec (headless, isolated);
the script VALIDATES structure (entity counts, field presence, enum
membership, relation integrity), retries once on failure, then writes
data.json+data.js(window global) + prints aggregate seeds.
- grok-4.6 authors realistic records for the spec (headless, isolated);
the script VALIDATES structure (entity counts, field presence, enum
membership, relation integrity), retries once on failure, then writes
- Images:
node scripts/generate-task-assets.mjs --spec <images-spec> --out <assets-dir>- grok image_gen, paced, self-healing auth sync, per-file sha manifest.
- Seal: record data.json sha + assets-manifest in the task fixture and in
every prepared cell's
cell.json.
Rules
- Deterministic where possible; all sample data labeled fictional in a
disclosurestring carried inside the dataset itself. - Never real brands/people; Korean-locale tasks use Korean-plausible fictional names.
- Aggregate expectations for data-fidelity audits are DERIVED from the sealed dataset at audit time, never hardcoded.
- KPI terms used in briefs must be DEFINED in the brief (lesson: the "open cases" ambiguity in wholesale-2026-08-18).
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.
- 1mo ago First seen · 35 lines · 0 tokens per session scan A cafe2fe338ff
bench-fixture-gen is a skill published in the GitHub repository kwakseongjae/oh-my-design (548 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 429 tokens. 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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