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 skeletorflet/opencode-supreme-setup --skill hatch-petgit clone --depth 1 https://github.com/skeletorflet/opencode-supreme-setupWrote 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/skeletorflet/opencode-supreme-setup/hatch-pet)<a href="https://agentmods.dev/skills/skeletorflet/opencode-supreme-setup/hatch-pet"><img src="https://agentmods.dev/badge/skills/skeletorflet/opencode-supreme-setup/hatch-pet/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/skeletorflet/opencode-supreme-setup/hatch-pet"><img src="https://agentmods.dev/badge/skills/skeletorflet/opencode-supreme-setup/hatch-pet.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 | $0.00114 | $0.05260 |
| Opus 5 | $0.00057 | $0.02630 |
| Sonnet 5 | $0.00023 | $0.01052 |
| Haiku 4.5 | $0.00011 | $0.00526 |
Grade A, and why
hatch-pet scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
98% identical to hatch-pet — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hatch Pet
Open Design integration. This is the unmodified Codex
hatch-petskill, vendored underskills/hatch-pet/so any Open Design agent can run it. After the skill finishes packaging, the resultingspritesheet.webp(under${CODEX_HOME:-$HOME/.codex}/pets/<pet-name>/) can be imported into the floating pet companion via Settings → Pets → Import Codex sprite. The import flow auto-detects the 8×9 /192×208atlas and lets the user pick which animation row to play (idle, running-right, waving, …).
Overview
Create a Codex-compatible animated pet from a concept, one or more reference images, or both. This skill owns pet-specific prompt planning, animation rows, frame extraction, atlas geometry, QA, previews, and packaging. It delegates visual generation to $imagegen.
User-facing inputs are optional. If the user omits a pet name, infer one from the concept or reference filenames; if that is not possible, choose a short appropriate name. If the user omits a description, infer one from the concept or references. If the user omits reference images, generate the base pet from text first, then use that base as the canonical reference for every animation row.
Generation Delegation
Use $imagegen for all normal visual generation.
Before generating base art, row strips, or repair rows, load and follow the installed image generation skill:
${CODEX_HOME:-$HOME/.codex}/skills/.system/imagegen/SKILL.md
Do not call the Image API directly for the normal path. Let $imagegen choose its own built-in-first path and its own CLI fallback rules. If $imagegen says a fallback requires confirmation, ask the user before continuing.
When invoking $imagegen from this skill, pass the generated pet prompt as the authoritative visual spec. Do not wrap it in the generic $imagegen shared prompt schema and do not add extra polish, hero-art, photo, product, or illustration-style augmentation. Pet prompts should stay terse, sprite-specific, and digital-pet oriented; only add role labels for input images and any essential user constraint.
What ships with it
24 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.
- .openskills.json 194 B
- agents/openai.yaml 560 B
- LICENSE.txt 11 KB
- open-design.json 2.3 KB
- README.md 2.6 KB
- references/animation-rows.md 1.4 KB
- references/codex-pet-contract.md 788 B
- references/qa-rubric.md 3.2 KB
- scripts/compose_atlas.py 5.1 KB runs code
- scripts/derive_running_left_from_running_right.py 4.8 KB runs code
- scripts/extract_strip_frames.py 10 KB runs code
- scripts/finalize_pet_run.py 14 KB runs code
- scripts/generate_pet_images.py 10 KB runs code
- scripts/inspect_frames.py 8.3 KB runs code
- scripts/make_contact_sheet.py 2.9 KB runs code
- scripts/package_custom_pet.py 3.4 KB runs code
- scripts/pet_job_status.py 4.0 KB runs code
- scripts/prepare_pet_run.py 27 KB runs code
- scripts/queue_pet_repairs.py 6.6 KB runs code
- scripts/record_imagegen_result.py 7.7 KB runs code
- scripts/render_animation_videos.py 4.1 KB runs code
- scripts/render_animation_videos.sh 152 B runs code
- scripts/test_generate_pet_images.py 5.0 KB runs code
- scripts/validate_atlas.py 4.7 KB runs code
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.
- 6d ago First seen · 355 lines · 114 tokens per session scan A 5dacdfa3d1dd
hatch-pet is a skill published in the GitHub repository skeletorflet/opencode-supreme-setup (47 stars, last pushed 3mo ago), licensed MIT. It adds 114 tokens to every session and 5,260 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to hatch-pet, differing in 7 lines, and is treated as a copy.
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