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 PangenomeAI/academic-skills-food-nutrition --skill food-deep-researchgit clone --depth 1 https://github.com/PangenomeAI/academic-skills-food-nutritionWrote 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/pangenomeai/academic-skills-food-nutrition/food-deep-research)<a href="https://agentmods.dev/skills/pangenomeai/academic-skills-food-nutrition/food-deep-research"><img src="https://agentmods.dev/badge/skills/pangenomeai/academic-skills-food-nutrition/food-deep-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.
<a href="https://agentmods.dev/skills/pangenomeai/academic-skills-food-nutrition/food-deep-research"><img src="https://agentmods.dev/badge/skills/pangenomeai/academic-skills-food-nutrition/food-deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00166 | $0.02120 |
| Opus 5.5 | $0.00066 | $0.00848 |
| Sonnet 5.5 | $0.00033 | $0.00424 |
| Haiku 4.5 | $0.00017 | $0.00212 |
Grade A, and why
food-deep-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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep-Research — Source-Validated Literature Review Engine
Answer a hard question properly and hand back a written, formatted, integrity-
checked literature review — not just notes. Scope → design → discover → screen
by journal ranking → validate sources → extract & verify evidence → synthesize →
stress-test → write → review-loop → final report. Original work; architecture
informed by open community food-deep-research skills (see the repo README
Acknowledgements). Usable standalone, or as the deep-dive engine called by
food-research.
Modes
- quick brief — scope → discover → screen (Tier 1) → light synthesis → short sourced answer. Skips the full validation/compile/review loop.
- full — the default: the complete 12-subagent pipeline below with the iterate-to-saturation and compile↔review loops, ending in a finished review.
Subagent team (dispatch via the Agent tool)
| # | Subagent | Job |
|---|---|---|
| 1 | research_scope |
Comprehensive scope brief: background, problem, significance, central + sub-questions, concepts, boundaries, success criteria. |
| 2 | research_architect |
Methodology blueprint: review type, search strategy, inclusion criteria, analytical framework, reporting standard, stopping criteria. |
| 3 | investigator |
Pass 1 discover candidate sources; Pass 2 extract evidence from validated sources only (parallel per sub-question). |
| 4 | source_screener |
Prioritize candidates by journal ranking (Tier 1 Q1/Q2 + Nature/Science/Cell + other-discipline Q1/Q2; Tier 2 Q3; avoid Tier 4). |
| 5 | source_verifier |
Validate each prioritized source (existence/DOI, venue legitimacy, retraction, predatory, methodology, COI) → Source Quality Matrix. |
| 6 | bibliography |
Deduplicate + format references (APA 7.0 default, or target-journal style via journal-selector); build the citation map + .bib/.ris. |
| 7 | claim_verifier |
Verify each load-bearing claim against its validated source; classify fact/hypothesis/contested/speculation. |
| 8 | synthesizer |
Evidence matrix, thematic synthesis, conflict reconciliation, evidence grading, coverage advisory, gap agenda, narrative arc. |
| 9 | critic |
Devil's advocate on the synthesis; loop back to investigate if gaps. |
| 10 | compiler |
Write & format the literature-review draft (APA 7.0 / target journal); cite by key only; no fabrication. |
| 11 | editor |
Editorial review of the draft (5 weighted dimensions, verdict + prioritized feedback). |
| 12 | ethics_reviewer |
Integrity/ethics review of the draft (citation integrity, faithful representation, bias, COI, disclosure). |
What ships with it
13 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.
- agents/bibliography.md 1.9 KB
- agents/claim_verifier.md 1.6 KB
- agents/compiler.md 4.3 KB
- agents/critic.md 1.4 KB
- agents/editor.md 1.8 KB
- agents/ethics_reviewer.md 1.9 KB
- agents/investigator.md 2.7 KB
- agents/research_architect.md 2.4 KB
- agents/research_scope.md 2.1 KB
- agents/source_screener.md 1.8 KB
- agents/source_verifier.md 2.5 KB
- agents/synthesizer.md 2.5 KB
- references/reasoning-and-fallacies.md 1.9 KB
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.
- 1mo ago First seen · 113 lines · 166 tokens per session scan A 8b03c0a2f645
food-deep-research is a skill published in the GitHub repository PangenomeAI/academic-skills-food-nutrition (38 stars, last pushed 1mo ago), licensed MIT. It adds 166 tokens to every session and 2,120 once invoked, about $0.0007 per session on Opus 5.5. 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.
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