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ingredient-research

ingredient-research is a skill for Claude Code from coleschaffer/copywritingskills-rmbc. It costs 32 tokens per session (1,454 once invoked), scanned A, original, MIT.

A research guide for checking evidence about ingredients in products such as supplements, skincare, and food. It gathers study results, dosage information, how ingredients work, and sources that can support product claims.

In plain words
What is it for?
Use it to research a product's ingredients, verify claims, find studies, and prepare cited evidence for later product writing.
Why use it?
It helps separate specific, supported claims from unsupported statements such as saying a product is simply “clinically proven.”

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter.

Part of the rmbc-skills plugin — 42 skills shipped together

not rated 30repo 5mo ago A scan 32 tokens original MIT

Good fit Use it to research a product's ingredients, verify claims, find studies, and prepare cited evidence for later product writing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/coleschaffer/copywritingskills-rmbc/ingredient-research
View source ↗ coleschaffer/copywritingskills-rmbc
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 coleschaffer/copywritingskills-rmbc --skill ingredient-research
Clone the repo
git clone --depth 1 https://github.com/coleschaffer/copywritingskills-rmbc

Made for: Claude Code.

Or install rmbc-skills, the plugin that ships this one along with the rest of its 42 skills.

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 ingredient-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/coleschaffer/copywritingskills-rmbc/ingredient-research/github.svg)](https://agentmods.dev/skills/coleschaffer/copywritingskills-rmbc/ingredient-research)
Your own site
<a href="https://agentmods.dev/skills/coleschaffer/copywritingskills-rmbc/ingredient-research"><img src="https://agentmods.dev/badge/skills/coleschaffer/copywritingskills-rmbc/ingredient-research/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 ingredient-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/coleschaffer/copywritingskills-rmbc/ingredient-research"><img src="https://agentmods.dev/badge/skills/coleschaffer/copywritingskills-rmbc/ingredient-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,454 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 $0.00032 $0.01454
Opus 5 $0.00016 $0.00727
Sonnet 5 $0.00006 $0.00291
Haiku 4.5 $0.00003 $0.00145

Measured 11d ago against content hash 85c6465c70fe, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ingredient-research 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 11d 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.

skills/ingredient-research/SKILL.md · 153 lines

How it starts

The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ingredient-research

Purpose

Systematic ingredient-level research tool for the "R" in RMBC. Gathers clinical studies, dosage data, bioavailability metrics, mechanism of action details, and DR-ready proof points per ingredient. Specificity beats persuasion — "94% improvement in a 30-day double-blind trial (n=120)" converts better than "clinically proven." Output feeds directly into mechanism ideation and copy writing.

Inputs

Input Required Description
product_name Yes Product or brand name
ingredients Yes List of ingredients to research (comma-separated or bulleted)
claims No Specific marketing claims to validate or find evidence for
product_category No supplement (default), skincare, food, other

Execution Protocol

Step 1 — Load Framework Context

Read rmbc-context/SKILL.md for RMBC methodology overview. This skill implements Pillar 4 of the Research phase: Ingredient Research.

Step 2 — Per-Ingredient Research Loop

For each ingredient in the list, systematically gather:

  1. Identity & Basics

    • Full compound name, common aliases, standardized form (if applicable)
    • Typical dosage range (clinical vs commercial)
    • Bioavailability considerations (absorption rate, delivery method impact)

  2. Clinical Evidence

    • Search for: randomized controlled trials, meta-analyses, peer-reviewed studies
    • Capture: author(s), year, journal, sample size, duration, key finding
    • Prioritize: human trials over animal/in-vitro, larger sample sizes, recent studies
    • Note patent numbers and clinical trial IDs (NCT numbers) when found

  3. Mechanism of Action

    • How the ingredient works at a biological/chemical level
    • Pathway or system it targets (e.g., "inhibits 5-alpha reductase," "upregulates AMPK")
    • Why this mechanism matters to the end consumer (plain-language translation)

  4. DR-Ready Proof Points

    • Extract specific, citable statistics and outcomes
    • Translate findings into compliant claim language
    • Flag any FTC/FDA compliance considerations for the claim type

Read the full file on GitHub · 153 lines

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. 11d ago First seen · 153 lines · 32 tokens per session scan A 85c6465c70fe

Subscribe to this mod's changes

ingredient-research is a skill published in the GitHub repository coleschaffer/copywritingskills-rmbc (30 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 1,454 once invoked, about $0.0002 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 2026-08-30.

ResearchScientific
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