FlowKit is a standalone system that uses a Chrome extension to connect AI agents to Google Flow for generating images and videos, including text-to-video and image-to-video work. It is for people who want to create video content through Google Flow rather than operate its web interface manually. The catalogue entries provide commands and instructions for working with FlowKit.
Borrowing it
Nothing to install: this file belongs to crisng95/flowkit. 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/crisng95/flowkit/main/AGENTS.mdgit clone --depth 1 https://github.com/crisng95/flowkitWrote 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/crisng95/flowkit/agents-md)<a href="https://agentmods.dev/instructions/crisng95/flowkit/agents-md"><img src="https://agentmods.dev/badge/instructions/crisng95/flowkit/agents-md/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/instructions/crisng95/flowkit/agents-md"><img src="https://agentmods.dev/badge/instructions/crisng95/flowkit/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.02465 | $0.02465 |
| Opus 5.5 | $0.00986 | $0.00986 |
| Sonnet 5.5 | $0.00493 | $0.00493 |
| Haiku 4.5 | $0.00247 | $0.00247 |
Grade A, and why
flowkit AGENTS.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 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.
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 How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Flow Kit — Codex CLI Instructions
Base URL: http://127.0.0.1:8100
Pre-flight
Before ANY workflow:
curl -s http://127.0.0.1:8100/health
# Flow mode must return: {"extension_connected": true}
# Assistant mode (MEDIA_PROVIDER=assistant or provider=assistant per request):
# extension_connected may be false — no Chrome extension needed.
# Check provider status instead: GET /api/providers/status
Critical Rules (MUST follow)
- Media ID is always UUID — format
xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx. Never useCAMS.../ base64 strings. - Scene prompts = ACTION only — never describe character appearance. Reference images handle visual consistency via
imageInputs. - All reference images must exist before scene images — verify every entity has
media_idbefore generating scene images. - No throwaway scripts — NEVER write Python, shell, or any script file to loop over API requests. Use
POST /api/requests/batchto submit all requests at once, then pollGET /api/requests/batch-status. The server throttles automatically. - Locations use landscape, characters use portrait — reference image orientation depends on entity type.
- UUID extraction — if a response gives
CAMS...instead of UUID, extract UUID from thefifeUrlin the response URL:/image/{UUID}?.... - Cascade on regen — regenerating an image auto-clears downstream video + upscale.
- REGENERATE vs GENERATE —
GENERATE_*skips if already COMPLETED.REGENERATE_*always runs (clears + regenerates). - Image Material required — every project needs a
materialfield (e.g.realistic,3d_pixar,anime). List available:GET /api/materials. - Server handles throttling (per provider) — each media provider declares its own limits (Flow: max 5 concurrent + 10s cooldown; assistant: max 2 concurrent, no cooldown). Submit ALL requests via
/batch; do NOT manually stagger or loop. Check effective limits:GET /api/providers/status. - Video prompts use sub-clip timing — structure 8s video as time segments:
0-3s: [action]. 3-6s: [action]. 6-8s: [action]. - Character dialogue in sub-clips — embed speech in quotes:
Luna says "Goodnight."Max 10-15 words per character per 2-3s segment. - Scenes are mutable — use
PATCH /api/scenes/{sid}to updateprompt,video_prompt,narrator_text,character_namesafter creation. Don't delete and recreate — patch instead. - 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.
- Real-people bypass — when characters are based on real famous people (politicians, celebrities, military leaders), NEVER use their real name as entity
nameor anywhere indescription,image_prompt,prompt, orvideo_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_textmay use real titles/roles for storytelling but real names never flow into image/video generation. Keep areal_referencemapping in the project plan file (.omc/research/) for internal tracking. - Review before upscale — ALWAYS run
/fk-review-video(light mode) after video generation, before upscaling. Scenes scoring < 7.5 getvideo_promptupdated from review errors, then regen video. Max 2 review-regen cycles.
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 Changed · +5 lines · +108 tokens per session feb08b2efa70
- 1mo ago Changed · +4 lines · +84 tokens per session 9f9bb1dee125
- 1mo ago Changed · +10 lines · +250 tokens per session 537aa67e74b0
- 2mo ago First seen · 106 lines · 2,023 tokens per session scan A 28f287fc4754
flowkit AGENTS.md is an instructions file published in the GitHub repository crisng95/flowkit (1,125 stars, last pushed 2d ago), licensed MIT. It adds 2,465 tokens to every session, about $0.0099 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
flowkit AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| flowkit AGENTS.mdcrisng95/flowkit | Instructions file | 1.1k | 2d ago | MIT | A | 2,465 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |