Borrowing it
Nothing to install: this file belongs to gregcastro23/WhatToEatNext. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/gregcastro23/WhatToEatNext/master/GEMINI.mdgit clone --depth 1 https://github.com/gregcastro23/WhatToEatNextWrote 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/instructions/gregcastro23/whattoeatnext/gemini-md)<a href="https://agentmods.dev/instructions/gregcastro23/whattoeatnext/gemini-md"><img src="https://agentmods.dev/badge/instructions/gregcastro23/whattoeatnext/gemini-md.svg" alt="Measured on agentmods" height="20"></a>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 | $0.02411 | $0.02411 |
| Opus 5 | $0.01205 | $0.01205 |
| Sonnet 5 | $0.00482 | $0.00482 |
| Haiku 4.5 | $0.00241 | $0.00241 |
Grade A, and why
WhatToEatNext GEMINI.md 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 8d 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WhatToEatNext - AI Assistant Guide (Alchm.kitchen)
Version: 3.4.0 | Last Updated: July 12, 2026
Project Overview
WhatToEatNext is a sophisticated culinary recommendation system that combines alchemical principles, astrological data, and elemental harmony to provide personalized food recommendations. The site is branded as Alchm.kitchen.
We operate a three-project loop:
- alchm.kitchen (WTEN): The core Next.js user-facing platform, deployed on Vercel.
- api.agents.alchm.kitchen (PA Backend): The Planetary Agents Python service owning agent personas, orchestration, and LLM recipe generation.
- agents.alchm.kitchen (PA UI): The Planetary Agents Next.js UI.
Current Project Status (July 2026 - v3.4.0)
🔮 PHILOSOPHER'S STONE AGENT FORGING & DYNAMIC CHAT
- End-to-End Forging: Created a user interface at
/philosophers-stoneenabling users to forge custom agents dynamically using birth details, name, and dominant elements. - Agent Ignition & Persona Generation: Implemented a dynamic API route at
/api/agent-forge/igniteto initialize custom personas and compute Sacred 7 stats using exact alchemical properties. The route writes the natal chart directly to the canonicaluser_profiles.natal_chartcolumn to align with the core database schema. - Context-Aware Vector Chat: Integrated OpenAI embeddings (
src/lib/embeddings/openaiEmbeddings.ts) and database migrations (database/init/59-recipe-embeddings.sql) to enable dynamic chat sessions with forged agents, complete with a recipe embedding backfill script. - Sacred 7 Stats Engine: Hardened alignment calculations (
src/lib/sacred-7-stats.ts) and derived attributes (diurnal balance, planetary aspects, dignity) to drive agent conversational behavior.
🧪 LAB PAGE ALCHEMICAL STATS FIXES
- Lab page stats panel "AWAITING BACKEND": Resolved the issue where the
/labpage showed missing natal stats for onboarded users by implementing a robust fallback inrowToUserWithProfileto load natal charts from the legacyusers.profileJSONB column if the column-level data is null. - Sign Case Mismatch: Corrected
calculateAlchemicalStatewhere sign properties lookup failed due to casing mismatches, restoring accurate alchemical and elemental calculation. - Onboarding CTA: Updated the lab page's login prompt to guide logged-in users with empty birth details to complete onboarding.
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.
- 8d ago First seen · 121 lines · 2,411 tokens per session scan A 042a1d2dd0f3
WhatToEatNext GEMINI.md is an instructions file published in the GitHub repository gregcastro23/WhatToEatNext (0 stars, last pushed today), licensed MIT. It adds 2,411 tokens to every session, about $0.0121 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.
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