AllNutrition
Alireza Faghaninia v1.0.2
AllNutrition — Evidence-Based Nutrition & Longevity Research Get clear, cited answers grounded in peer-reviewed nutrition, health, and longevity research. AllNutrition.info distills tens of thousands of scientific studies into practical, understandable insights—without industry-sponsored research or manufactured controversy. Ask AllNutrition about nutrition, supplements, diet, metabolism, healthy aging, longevity, disease prevention, sports and exercise nutrition, and other evidence-based health topics. Get research-backed summaries, study citations, comparisons, and explanations of what the scientific evidence actually shows. Use AllNutrition to: - Find and understand peer-reviewed nutrition research - Evaluate claims about foods, diets, supplements, and nutrients - Explore longevity and healthy-aging research - Compare competing nutrition claims and interventions - Separate strong evidence from weak or uncertain findings - Get concise answers with supporting scientific citations Ask a question in plain English and AllNutrition turns the relevant research into a clear, evidence-focused answer.
Language: English · Automatically detected from descriptions.
Package details
Publisher declarations from the archived package. These are separate from our research and the live service's terms.
- Package author
- Alireza Faghaninia
Package observed Sep 30, 2026.
Files & skills
File archives
Skill instructions
compact-references2.43 KB
---
name: compact-references
description: Produce a compact, numbered reference list from AllNutrition results. Use when the user asks for "the references", "the sources", "a bibliography", or a copy-pasteable/shareable citation list — either for an answer AllNutrition already gave in this conversation or for a fresh topic.
---
# Compact reference list
Turn AllNutrition source lists into a short, numbered, plain-text bibliography
that fits in a tight character budget without losing any links.
## Input
One of:
- A prior `ask_nutrition` or `search_references` result in this conversation
whose `sources` the user now wants listed.
- A fresh topic ("give me references on magnesium and sleep") with no prior
result — call `search_references` with the topic first (default
`max_results`, add `published_after` only if the user asked for recent work).
## Procedure
1. Collect the sources. Use only the `sources` array returned by AllNutrition
tools. Never add sources from memory or the open internet, and never invent,
guess, or "fix" a URL — reproduce each URL exactly as returned.
2. Deduplicate by URL, keeping the first occurrence. If the list annotates an
existing answer's citations, keep the numbering the answer used so the
numbers still match; otherwise number from 1 in the returned order.
3. Render one line per source in exactly this shape:
```
References:
1. Title https://example.org/...
2. Title https://example.org/...
```
4. Fit the whole block into the character budget: 4,900 characters total
unless the user gives a different limit. Shorten only the titles, never the
URLs. Truncate every title at the same maximum length and append `...` to
any title you cut; pick the largest uniform title length that keeps the
whole block under budget. With a typical list of 10 sources, full titles
usually fit — only shorten when they don't.
## Output
Only the `References:` block, ready to copy. No commentary, no verbatim
excerpts or quotes from the sources, no markdown link syntax (bare URLs are
the point — they survive copy-paste into plain-text contexts).
## Boundaries
- If there are no sources to list (the tool returned none, or the prior answer
had none), say so — do not fill the gap with sources of your own.
- If the user asks for full abstracts or verbatim passages, explain that
AllNutrition returns AI-written summaries, not verbatim source text, and
offer the source links instead.
evidence-comparison2.48 KB
---
name: evidence-comparison
description: Compare two or more nutrition claims, diets, supplements, or interventions using AllNutrition's cited evidence. Use for "X vs Y" questions, "which is better for…", or whenever the user wants competing claims evaluated side by side rather than a single answer.
---
# Evidence comparison
Put competing nutrition claims side by side with the evidence behind each one,
so the user sees not just which option looks better but how sure the science
actually is.
## Input
Two or more named options and the outcome they should be compared on — e.g.
"creatine vs beta-alanine for strength", "Mediterranean vs low-carb for
longevity". If the outcome is missing, ask for it before calling any tool: a
comparison without an outcome is not answerable.
## Procedure
1. Call `ask_nutrition` once per option, phrasing each question identically
except for the option ("Does X improve <outcome>?"). Identical phrasing
keeps the answers comparable. Use `deep_research: true` only when the user
explicitly asks for a deep or comprehensive review — it takes minutes per
call, so mention the wait before starting.
2. Read each answer's `evidence_strength` (strong | moderate | limited |
insufficient) and `consensus_level` (high | moderate | mixed | low). These
labels are the comparison's backbone — never omit or soften them.
3. Compare only what the returned evidence supports. If the evidence for the
two options was studied in different populations or doses, say so instead
of forcing a winner.
## Output
1. A one-or-two-sentence verdict up front, hedged to match the weaker side's
evidence labels.
2. A table with one row per option: what the evidence shows, `evidence
strength`, `consensus`.
3. A single combined reference list for all options, deduplicated by URL, in
the compact numbered format (`n. Title URL`) — cite only sources the tools
returned.
4. A closing note naming the biggest gap or caveat (e.g. "no head-to-head
trials; both compared to placebo separately").
## Boundaries
- Never declare a winner when both sides are `limited`/`insufficient` or
consensus is `mixed`/`low` — say the evidence cannot separate them.
- Describe what the research shows for populations, not what this user should
personally do; nutrition evidence is not a personal prescription.
- If the user adds their own claimed study ("I read that X cures Y"), check it
against `search_references` results rather than accepting or contradicting
it from memory.
Technical details
- First seen
- Sep 30, 2026 · 22:02 UTC
- Last seen
- Oct 1, 2026 · 12:00 UTC
- Collection status
- Collected
plugin_asdk_app_6a7a17e926288191901f3ecec137da0e
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