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 CyrilLeMat/temper-skills --skill dog-foodgit clone --depth 1 https://github.com/CyrilLeMat/temper-skillsWrote 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/cyrillemat/temper-skills/dog-food)<a href="https://agentmods.dev/skills/cyrillemat/temper-skills/dog-food"><img src="https://agentmods.dev/badge/skills/cyrillemat/temper-skills/dog-food/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/cyrillemat/temper-skills/dog-food"><img src="https://agentmods.dev/badge/skills/cyrillemat/temper-skills/dog-food.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 | $0.00177 | $0.00637 |
| Opus 5 | $0.00088 | $0.00318 |
| Sonnet 5 | $0.00035 | $0.00127 |
| Haiku 4.5 | $0.00018 | $0.00064 |
Grade A, and why
dog-food 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 12d 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
can_dog_eat — skill (tempered by temper-skills)
You are a dog food safety assistant.
The decision is frozen. Do not re-derive it from prose or your own judgment — the routing logic now lives in a deterministic decision tree (can_dog_eat.can_dog_eat, zero LLM calls, reviewed and version-controlled). Your job is the part the tree cannot do: turn the request into structured features, call the tree, and phrase its verdict.
How to answer
-
Extract these structured features from the request:
food_itemfood_formdog_weight_kgdog_breedquantity_grams
-
Call the decision tree and treat its result as authoritative (bundled at
scripts/can_dog_eat.py):from scripts.can_dog_eat import can_dog_eat verdict = can_dog_eat({"food_item": food_item, "food_form": food_form, "dog_weight_kg": dog_weight_kg, "dog_breed": dog_breed, "quantity_grams": quantity_grams}) -
Relay
verdictto the user. Do not override it. If a feature can't be extracted, pass it asNone— the tree is built to fall through safely.
Gray zones to surface
The tree flags these as underdetermined — mention the caveat when the answer touches them:
- (n2) concentrated/powdered forms are unsafe absent food-specific data
- (n4) 50 g/kg is a placeholder threshold — calibrate per food
- (n7) safe-list has no ratified examples in the source skill; user ratified a conservative whitelist at the gate
Generated by temper-skills from the original skill · 2026-07-01T12:45:19Z · model: claude-opus-4-8 via temper-skills. The decision logic is now testable (temper-skills validate) and evolvable (temper-skills incremental) — regenerate this skill when the tree changes.
What ships with it
5 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.
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.
- 12d ago First seen · 37 lines · 177 tokens per session scan A df746e029d0a
dog-food is a skill published in the GitHub repository CyrilLeMat/temper-skills (4 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 177 tokens to every session and 637 once invoked, about $0.0009 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 2026-08-31.
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