# Dog Food

> Frozen, deterministic decision (no LLM): maps food_item, food_form, dog_weight_kg, dog_breed, quantity_grams to one of no — toxic to dogs, never feed, no — concentrated form multiplies toxin and fat dose per gram, no — low-fat/sugar-free peanut butter may contain xylitol; check the label, caution — large dose relative to body weight, unknown — a valid dog weight is required to assess this quantity, yes — standard peanut butter is safe in moderation, if xylitol-free, yes — safe in moderation, yes — apple flesh only; never the core or seeds, no — when in doubt, do not feed; verify with a vet. Use when this decision must be made consistently and auditably — extract the features, call can_dog_eat(), and relay its verdict without overriding it.

- Skill: `cyrillemat/dog-food` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add cyrillemat/dog-food`
- Raw SKILL.md: https://api.skillmd.com/api/skills/cyrillemat/dog-food/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: CyrilLeMat (https://skillmd.com/u/cyrillemat)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/cyrillemat/dog-food

---


# 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

1. Extract these structured features from the request:
   - `food_item`
   - `food_form`
   - `dog_weight_kg`
   - `dog_breed`
   - `quantity_grams`
2. Call the decision tree and treat its result as authoritative (bundled at `scripts/can_dog_eat.py`):

   ```python
   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})
   ```
3. Relay `verdict` to the user. **Do not override it.** If a feature can't be extracted, pass it as `None` — 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.