flowkit GEMINI.md

Instructions for a Google Flow agent used through the Gemini command-line tool and a local service. They define required checks, media identifiers, image orientations, batching, and regeneration behavior.

In plain words
What is it for?
Checking the local service, preparing reference images, submitting batch requests, polling their status, and regenerating images while handling dependent video or upscale outputs.
Why use it?
They enforce the service's required workflow and identifier formats, reducing failed requests caused by missing references or incorrect downstream assets.

Instructions file for Gemini CLI

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.

agentmods
npx agentmods add instructions/crisng95/flowkit/gemini-md
Clone the repo
git clone --depth 1 https://github.com/crisng95/flowkit

Made for: Gemini CLI.

Per session 2,022 This file is loaded in full into every session.
When invoked 2,022 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
Origin 98% copy Near-identical to another mod 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 $0.02022 $0.02022
Opus 5 $0.01011 $0.01011
Sonnet 5 $0.00404 $0.00404
Haiku 4.5 $0.00202 $0.00202

Measured 2d ago against content hash ee628330b359, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

flowkit GEMINI.md scanned grade A with 1 finding 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 2d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s http://127.0.0.1:8100/health
Origin

This is a copy

98% identical to flowkit AGENTS.md — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

GEMINI.md · 106 lines

How it starts

The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Google Flow Agent — Gemini CLI Instructions

Base URL: http://127.0.0.1:8100

Pre-flight

Before ANY workflow:

curl -s http://127.0.0.1:8100/health
# Must return: {"extension_connected": true}

Critical Rules (MUST follow)

  1. Media ID is always UUID — format xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx. Never use CAMS... / base64 strings.
  2. Scene prompts = ACTION only — never describe character appearance. Reference images handle visual consistency via imageInputs.
  3. All reference images must exist before scene images — verify every entity has media_id before generating scene images.
  4. No throwaway scripts — NEVER write Python, shell, or any script file to loop over API requests. Use POST /api/requests/batch to submit all requests at once, then poll GET /api/requests/batch-status. The server throttles automatically.
  5. Locations use landscape, characters use portrait — reference image orientation depends on entity type.
  6. UUID extraction — if a response gives CAMS... instead of UUID, extract UUID from the fifeUrl in the response URL: /image/{UUID}?....
  7. Cascade on regen — regenerating an image auto-clears downstream video + upscale.
  8. REGENERATE vs GENERATEGENERATE_* skips if already COMPLETED. REGENERATE_* always runs (clears + regenerates).
  9. Image Material required — every project needs a material field (e.g. realistic, 3d_pixar, anime). List available: GET /api/materials.
  10. Server handles throttling — worker enforces max 5 concurrent requests + 10s cooldown. Submit ALL requests via /batch; do NOT manually stagger or loop.
  11. Video prompts use sub-clip timing — structure 8s video as time segments: 0-3s: [action]. 3-6s: [action]. 6-8s: [action].
  12. Character dialogue in sub-clips — embed speech in quotes: Luna says "Goodnight." Max 10-15 words per character per 2-3s segment.
  13. Scenes are mutable — use PATCH /api/scenes/{sid} to update prompt, video_prompt, narrator_text, character_names after creation. Don't delete and recreate — patch instead.
  14. Fact-check before scripting — ALWAYS research events via web search before writing project stories, scene prompts, or narrator text. Facts (events, dates, names, operations, outcomes) MUST match real sources. Editorial opinion and analysis are allowed but must be framed as such. Never invent events, operation names, or statistics.
  15. Real-people bypass — when characters are based on real famous people (politicians, celebrities, military leaders), NEVER use their real name as entity name or anywhere in description, image_prompt, prompt, or video_prompt. AI image generators reject known public figures. Instead: (a) use a role-based alias as entity name (e.g. "Tổng Tư Lệnh" not "Trump", "Thủ Tướng Sắt" not "Netanyahu"), (b) describe physical appearance only — distinctive hair, face shape, build, clothing style — without naming who it is, (c) narrator_text may use real titles/roles for storytelling but real names never flow into image/video generation. Keep a real_reference mapping in the project plan file (.omc/research/) for internal tracking.
  16. Review before upscale — ALWAYS run /fk-review-video (light mode) after video generation, before upscaling. Scenes scoring < 7.5 get video_prompt updated from review errors, then regen video. Max 2 review-regen cycles.

Read the full file on GitHub · 106 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. 2d ago First seen · 106 lines · 2,022 tokens per session scan A ee628330b359

Subscribe to this mod's changes

flowkit GEMINI.md is an instructions file published in the GitHub repository crisng95/flowkit (613 stars, last pushed 14d ago), licensed MIT. It adds 2,022 tokens to every session, about $0.0101 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 98% identical to flowkit AGENTS.md, differing in 2 lines, and is treated as a copy.

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