dog-food

dog-food is a skill for Claude Code, Codex from CyrilLeMat/temper-skills. It costs 177 tokens per session (637 once invoked), scanned A, original, Apache-2.0.

A dog-food safety guide that uses fixed rules to judge whether a dog can eat a specified food, form, and amount.

In plain words
What is it for?
Use it to check foods such as peanut butter against a dog's size, breed, food form, and serving amount.
Why use it?
It avoids inconsistent guesses by applying the same decision rules every time and flags missing information safely.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to check foods such as peanut butter against a dog's size, breed, food form, and serving amount.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cyrillemat/temper-skills/dog-food
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 CyrilLeMat/temper-skills --skill dog-food
Clone the repo
git clone --depth 1 https://github.com/CyrilLeMat/temper-skills

Made for: Claude Code, 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 dog-food

README.md
[![agentmods](https://agentmods.dev/badge/skills/cyrillemat/temper-skills/dog-food/github.svg)](https://agentmods.dev/skills/cyrillemat/temper-skills/dog-food)
Your own site
<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.

agentmods 80×15 button for dog-food

Your own site · 80×15
<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>
Per session 177 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 637 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.
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 $0.00177 $0.00637
Opus 5 $0.00088 $0.00318
Sonnet 5 $0.00035 $0.00127
Haiku 4.5 $0.00018 $0.00064

Measured 12d ago against content hash df746e029d0a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

The scan reads SKILL.md. This mod also ships 4 executable files (assets/can_dog_eat.schema.py, scripts/can_dog_eat.py, scripts/test_can_dog_eat_ratified.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

examples/dog_food/output/dog-food/SKILL.md · 37 lines

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

  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):

    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.

Files

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.

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. 12d ago First seen · 37 lines · 177 tokens per session scan A df746e029d0a

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

anatomia-cc

ES: Te dice qué construir en Claude Code y te da el esqueleto de archivos: skill y en qué modo, subagente, hook, servidor MCP, plugin, rutina, artefacto, app con el Agent SDK, una línea en CLAUDE.md, o nada. Corré esto antes del primer archivo. Se dispara con «esto lo hago como skill o como agente», «necesito un MCP o…

Hainrixz/claude-anatomy · 267 tokens

grill-me-store-decisions

Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree, AND persist the full decision tree (selected + rejected options, recommendations, AND cost tradeoffs) to decision-tree.md in the current repo so choices can be revisited later. Use…

vbalasu/grill-me-store-decisions · 84 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

google-ads-audit

Google Ads account audit and business context setup. Use for account-health audits and business-context setup. Trigger on "audit my ads", "ads audit", "set up my ads", "onboard", "account overview", "how's my account", "ads health check", "what should I fix in my ads", or when the user is new to NotFair and hasn't run…

nowork-studio/notfair-plugin · 86 tokens

data-charts-tako

Search and visualize the world's data - get charts, insights, and embeddable knowledge cards for finance, economics, demographics, sports, and more.

gooseworks-ai/goose-skills · 35 tokens

webhook-management

Configure and validate CCAM webhook targets across supported chat, incident, automation, and generic providers. Use when listing provider requirements, creating or updating a target, scoping it to alert rules, sending a test notification, reviewing delivery history, or deleting a target.

hoangsonww/Claude-Code-Agent-Monitor · 56 tokens