Video Generation
bytedance/deer-flow
Generates short videos from a structured JSON prompt, optionally guided by a reference image used as the first or last frame.
Two-part gate for gflow-cli feature/fix work. An agent skill from ffroliva/gflow-cli.
$ npx skills add ffroliva/gflow-cli --skill live-verify -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ffroliva/gflow-cli live-verify --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ffroliva/gflow-cli.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/live-verify .claude/skills/live-verify && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "live-verify" agent skill from https://github.com/ffroliva/gflow-cli/tree/develop/skills/live-verify into .claude/skills/live-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "live-verify", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ffroliva/gflow-cli/tree/develop/skills/live-verifyType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ffroliva/gflow-cli --skill live-verify -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ffroliva/gflow-cli live-verify --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ffroliva/gflow-cli.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/live-verify .agents/skills/live-verify && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "live-verify" agent skill from https://github.com/ffroliva/gflow-cli/tree/develop/skills/live-verify into .agents/skills/live-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "live-verify", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ffroliva/gflow-cli --skill live-verify -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ffroliva/gflow-cli live-verify --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ffroliva/gflow-cli.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/live-verify .cursor/skills/live-verify && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "live-verify" agent skill from https://github.com/ffroliva/gflow-cli/tree/develop/skills/live-verify into .cursor/skills/live-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "live-verify", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ffroliva/gflow-cli.git --path skills/live-verify--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ffroliva/gflow-cli --skill live-verify -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ffroliva/gflow-cli live-verify --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ffroliva/gflow-cli.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/live-verify .gemini/skills/live-verify && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "live-verify" agent skill from https://github.com/ffroliva/gflow-cli/tree/develop/skills/live-verify into .gemini/skills/live-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "live-verify", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ffroliva/gflow-cli live-verifyInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ffroliva/gflow-cli --skill live-verify -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ffroliva/gflow-cli.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/live-verify .github/skills/live-verify && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "live-verify" agent skill from https://github.com/ffroliva/gflow-cli/tree/develop/skills/live-verify into .github/skills/live-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "live-verify", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ffroliva/gflow-cli --skill live-verify -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ffroliva/gflow-cli live-verify --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ffroliva/gflow-cli.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/live-verify .opencode/skills/live-verify && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "live-verify" agent skill from https://github.com/ffroliva/gflow-cli/tree/develop/skills/live-verify into .opencode/skills/live-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "live-verify", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
live-verifyTwo-part gate for gflow-cli feature/fix work. An agent skill from ffroliva/gflow-cli.
Live Verify is an agent skill from ffroliva/gflow-cli. Two-part gate for gflow-cli feature/fix work. Part 1 (Pre-flight): use when starting work on a gflow-cli feature or fix — confirms the checkout reflects current develop before investing effort. Part 2 (Live-verify): use before claiming gflow-cli work done, especially anything touching a generation code path (t2i/i2i/i2v/t2v/r2v) — requires live evidence against real Flow, not just offline tests.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Media & Creative, covering AI video generation. The repository describes itself as: Drive Google Flow from the command line: Veo video and Imagen images, scripted, batched and pipeline-ready. Ships an MCP server so coding agents can drive it too, giving you and… The licence is MIT.
2 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit cb6d501. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
gitpytestghFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use git and gh, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Live Verify loads about 2.3k tokens when it runs. Until then it costs about 103 tokens; SKILL.md has 1,169 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from ffroliva/gflow-cli at commit cb6d501, republished under its MIT licence (© ffroliva). 1,169 words, ~2,335 tokens.
.claude/skills/live-verify/SKILL.md (or your agent's skills folder)./gflow:live-verify — Live-verification enforcementgflow-cli reverse-engineers a blackbox: Google Flow. Offline checks (ruff, pyright,
unit/BDD tests) verify gflow-cli's own code does what it's supposed to; they cannot verify
Flow still behaves the way it was captured, because Flow is external and changes without
notice (see #174). This gate enforces two
things, both evidence-based (no claim without a fresh verification artifact — see the
superpowers:verification-before-completion skill):
develop before investing effort./code-review and
/ponytail:ponytail-review, before commit/PR): exercise the change against real Flow.Full design rationale:
docs/superpowers/specs/2026-07-19-live-verify-design.md.
Run before writing any code for a new feature/fix:
git fetch origin
git rev-parse --abbrev-ref HEAD
git rev-list --count HEAD..origin/develop
git log --oneline -5git rev-list --count HEAD..origin/develop is an asymmetric DAG set-difference — it counts
commits develop has that the current HEAD lacks, regardless of HEAD's own private
unmerged history. This is what catches a genuinely diverged stale branch, not just a
behind-by-fast-forward one.
git pull (on develop) or rebase/merge (on a feature
branch) before continuing.develop activity (a
smell for stale WIP — e.g. missing a function/guard that develop already has): stop and
surface it. Don't silently proceed, don't silently switch — name the divergence and ask the
user how to proceed.develop. The actual signal is "differs from develop in a
way that suggests staleness" (missing something develop has), not "differs by adding new
work on top of it." When in doubt, diff the specific file(s) about to be touched against
origin/develop's version before assuming they match:git diff origin/develop -- <path/to/file>"Live" means: drive the real generation commands (t2i, i2i, i2v, and siblings like
t2v/r2v where applicable) against a real authenticated Flow account, covering multiple
variations of the change — not one happy-path call. A change touching a generation code
path is default-in-scope; skipping this gate requires a named reason, not silence.
1. Define the live matrix. Before running anything, name explicitly:
mcp/tools.py → queue payload → worker/codec.py → request → daemon owns download and
recording). A CLI run does not exercise it. Decide per change whether the MCP path needs
its own live run, and if you skip it, say so with a reason. The cheap version is usually
enough: one queued MCP call on a credit-free operation proves the payload keys round-trip,
which is the hop that silently no-ops (#495). Offline parity tests cannot see this —
they never build a real payload and decode it.2. Check the cost tier for each variation — the tier follows the operation, not the command family:
create_entity, list_characters,
patch_entity at the API level; t2i/i2i themselves) are credit-free — run as
needed to cover the matrix without a separate confirm each time. Still mind WAF/volume
discipline: don't fire dozens of live calls back-to-back without surfacing it to the
user first.gflow character create --face-prompt generates real face/body images
and drives real image generation despite being "character CRUD" in name (zero credits, daily-capped); i2v and other
video-generation paths are always costed. Always get explicit operator go-ahead before
running a costed variation. Batch the ask: name what will run and why, once, not one
confirm per call.3. Run each variation, capture evidence per run. Use the release skill's actual 5-layer
ledger shape (skills/release/SKILL.md §4b), adapted per-field to what the change under
test produces:
| Layer | Evidence |
|---|---|
| File count | New file(s)/DB row(s) produced by the run |
| Magic bytes / field value | The specific artifact or field the change is supposed to affect (e.g. a real image's magic bytes, or de-tagged prompt text in the catalog) |
| Dimensions/shape | For media output: actual dimensions match the requested aspect ratio/model |
| Structlog invariants | The expected log event fired (e.g. mention_resolved, not mention_unresolved) |
| User-confirmable artifact | Real output a human could open and check (image/video file, size > 1024 bytes) |
Write this to a lightweight per-feature evidence note at tmp/live-verify/<feature-slug>.md
(gitignored — this is not the full docs/LIVE_VERIFICATION_vX.Y.Z.md release ceremony).
Fold it into the real LIVE_VERIFICATION doc when the feature ships in a release.
4. On pass: all matrix variations green — proceed to commit.
5. On fail: go to Failure-routing below.
1. Check for a known match first (costed failures only, to avoid an unnecessary
re-spend): grep KNOWN_ISSUES.md and open GitHub issues for a matching error signature.
gh issue list --repo ffroliva/gflow-cli --search "<error text>" --state all2. If no match, re-test once. Free for t2i/i2i — just re-run. For a costed failure,
re-testing needs the same operator confirm as any costed run.
3. Compare outcomes and route:
| Outcome | Route |
|---|---|
| Same failure, same code, no known-issue match | Real bug. Back to execution — fix it (use superpowers:systematic-debugging if the cause isn't obvious). Re-run this gate after the fix. |
| Different outcome, same code, no changes in between — OR a known-issue match | External flake. Do not loop trying to "fix" it. Record it in the evidence note (what failed, that it's not reproducible against unchanged code, link to the matching issue if any). Gate passes-with-caveat for this run. |
| The failure reveals the plan's premise was wrong (not a bug, not a flake) | Back to planning/design, not execution. Don't keep patching code against a wrong premise. |
4. Record every outcome in the evidence note — passes, fails, and flakes are all evidence, not just the final green state.
Main context or superpowers:subagent-driven-development — never a stateless one-shot
subagent. Diagnosing a live failure needs memory of what's already been tried; a fresh,
context-less subagent call breaks a spike-then-fix-then-retest loop.
Upon completing Live Verification:
/gflow:issue-resolve <N>)."/gflow:check (offline gates before commit), nor
pytest -m e2e (the e2e suite against a live profile), nor /gflow:doc-review
(release-time doc council) — it fills the gap between them.tmp/live-verify/ note; it
never runs pytest -m e2e. A PR touching a Flow surface owes BOTH: the e2e test is the
re-runnable regression, this ledger is the record of what was observed once, live. See
[[e2e-evidence-is-a-contributor-deliverable]] and CONTRIBUTING § Test categories.© ffroliva, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/live-verify of ffroliva/gflow-cli.
Open the folder on GitHubat commit cb6d501
Live Verify next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Live Verify this skillffroliva/gflow-cli | 264 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Video Generationbytedance/deer-flow | 83k | 4 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Video Shotseternityspring/reelbench-skills | 868 | 2 repos | ~1.8k | Automated safety check: Notes | Apache-2.0 | |
| Video Cover Imageitwanger/toBeBetterJavaer | 18k | — | ~3.3k | Automated safety check: Pass | None | |
| Seedancesongguoxs/seedance-prompt-skill | 2.9k | 1 repos | ~2.5k | Automated safety check: Pass | None | |
| HyperFrames Video Entry Pointheygen-com/hyperframes | 59k | 3 repos | ~5.2k | Automated safety check: Pass | Apache-2.0 |
bytedance/deer-flow
Generates short videos from a structured JSON prompt, optionally guided by a reference image used as the first or last frame.
eternityspring/reelbench-skills
拉片:把一条成片拆成逐镜头的分析表——每个镜头的时长、景别、类别、运镜、画面. An agent skill from eternityspring/reelbench-skills.
itwanger/toBeBetterJavaer
Generate matched 3:4, 16:9, and 4:3 short-video cover images from toBeBetterJavaer video scripts or AI/Java technical topics.
songguoxs/seedance-prompt-skill
This skill should be used when the user asks to "generate video prompts", "create Seedance prompts", "write video descriptions", mentions "Seedance", "seedance", "即梦", "即梦平台", "视频提示词", "视频生成"…
heygen-com/hyperframes
Entry point for making, editing and rendering videos from HTML compositions with HyperFrames, routing each request to the right workflow.
cclank/lanshu-create-ai-presenter-video
Turn a topic or finished script into a complete, publish-ready explainer video — led by an AI presenter from an authorized adult presenter image, or performed in one of nine visual explainer styles…
ffroliva/gflow-cli
A skill your agent uses when the user wants to drive Google Flow (Veo image-to-video, Veo text-to-video, Imagen / Nano Banana image generation) from the terminal or a script — including…
ffroliva/gflow-cli
A skill your agent uses when triaging a GitHub issue for gflow-cli — a reporter's bug claim, a freshly-filed issue, or deciding whether and how to act on one.
ffroliva/gflow-cli
A skill your agent uses when an assessed gflow-cli issue (verdict CONFIRMED-BUG or LIKELY-BUG) has localized, verifiable scope and should be driven to a fix.
ffroliva/gflow-cli
A skill your agent uses when the user wants a finished video out of gflow rather than a single clip — a scripted scene, a talking-head or dialogue piece, an explainer, a product montage, a story…
ffroliva/gflow-cli
Auto-fix lint and formatting, then report types and tests. An agent skill from ffroliva/gflow-cli.
ffroliva/gflow-cli
Use before cutting any gflow-cli release or after a major documentation change — systematic council-driven audit that combines a mechanical 7-section checklist with a 3-agent parallel review…
Categories
Two-part gate for gflow-cli feature/fix work. An agent skill from ffroliva/gflow-cli. Live Verify is an agent skill from ffroliva/gflow-cli. Two-part gate for gflow-cli feature/fix work.
Live Verify fits situations like: starting work on a gflow-cli feature; fix — confirms the checkout reflects current develop before investing effort.
Run `npx skills add ffroliva/gflow-cli --skill live-verify -a claude-code`. Or copy the skill folder (skills/live-verify in ffroliva/gflow-cli) into .claude/skills/live-verify in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ffroliva/gflow-cli --skill live-verify -a codex`. Or copy the skill folder (skills/live-verify in ffroliva/gflow-cli) into .agents/skills/live-verify in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ffroliva/gflow-cli --skill live-verify -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/live-verify, .gemini/skills/live-verify, .github/skills/live-verify and .opencode/skills/live-verify in your project.
Going by SKILL.md and its folder, Live Verify needs the command-line tools its instructions call (git, pytest and gh).
SKILL.md contains no URLs. Its commands use git and gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Live Verify is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Live Verify: Video Generation (bytedance/deer-flow, 83k stars), Video Shots (eternityspring/reelbench-skills, 868 stars), Video Cover Image (itwanger/toBeBetterJavaer, 18k stars) and Seedance (songguoxs/seedance-prompt-skill, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ffroliva (a GitHub user) maintains it in ffroliva/gflow-cli, which has 264 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on October 7, 2026.
Source: ffroliva/gflow-cli on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.