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 prime-skills/runcomfy-agent-skills --skill wan-2-7git clone --depth 1 https://github.com/prime-skills/runcomfy-agent-skillsWrote 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/prime-skills/runcomfy-agent-skills/wan-2-7)<a href="https://agentmods.dev/skills/prime-skills/runcomfy-agent-skills/wan-2-7"><img src="https://agentmods.dev/badge/skills/prime-skills/runcomfy-agent-skills/wan-2-7/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/prime-skills/runcomfy-agent-skills/wan-2-7"><img src="https://agentmods.dev/badge/skills/prime-skills/runcomfy-agent-skills/wan-2-7.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk 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 | $0.00156 | $0.02346 |
| Opus 5 | $0.00078 | $0.01173 |
| Sonnet 5 | $0.00031 | $0.00469 |
| Haiku 4.5 | $0.00016 | $0.00235 |
Grade A, and why
wan-2-7 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 12d 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 — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wan 2.7 — Pro Pack on RunComfy
runcomfy.com · Text-to-video · GitHub
Wan-AI's Wan 2.7 — flagship video model with multi-reference conditioning and audio-driven lip-sync — hosted on the RunComfy Model API.
npx skills add agentspace-so/runcomfy-skills --skill wan-2-7 -g
When to pick this model (vs siblings)
| You want | Use |
|---|---|
| Lip-sync video to an audio track you supply | Wan 2.7 (audio_url) |
| Multi-reference fine motion control | Wan 2.7 |
| Smooth transitions, accurate motion physics | Wan 2.7 |
| Currently-#1 blind-vote video model | HappyHorse 1.0 |
| Multi-modal cinematic with image+video+audio refs + in-pass voice generation | Seedance 2.0 Pro |
| Cinematic motion editing on existing footage | Kling Video O1 |
| Ultra-fast iteration | LTX 2 |
If the user said "Wan" / "Wan 2.7" / "wan-ai" / "alibaba video" explicitly, route here regardless.
Prerequisites
- RunComfy CLI —
npm i -g @runcomfy/cli - RunComfy account —
runcomfy loginopens a browser device-code flow. - CI / containers — set
RUNCOMFY_TOKEN=<token>instead ofruncomfy login.
Endpoints + input schema
wan-ai/wan-2-7/text-to-video
| Field | Type | Required | Default | Notes |
|---|---|---|---|---|
prompt |
string | yes | — | Up to ~5000 chars / ~1500 tokens. |
audio_url |
string | no | — | WAV/MP3, 3–30s, ≤15MB. Drives lip-sync. Omit → background music auto-generated. |
aspect_ratio |
enum | no | 16:9 |
16:9, 9:16, 1:1, 4:3, 3:4. |
resolution |
enum | no | 1080p |
720p or 1080p. |
duration |
enum | no | 5 |
2–15 (whole seconds). |
negative_prompt |
string | no | — | Up to 500 chars. Concrete issues to avoid. |
enable_prompt_expansion |
bool | no | true | Auto-rewrites short prompts. Disable for literal control. |
seed |
int | no | — | 0..2^31-1. Reuse for variants. |
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.
- 12d ago First seen · 186 lines · 156 tokens per session scan A 0c38b830e5a8
wan-2-7 is a skill published in the GitHub repository prime-skills/runcomfy-agent-skills (44 stars, last pushed 3mo ago), licensed MIT. It adds 156 tokens to every session and 2,346 once invoked, about $0.0008 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 2026-08-30.
Other skills, from other repositories
webgl-holographic-foil
A self-contained WebGL2 hero: thin-film interference over a crushed-foil surface whose palette shifts with the viewing angle; move the cursor to tilt the film.
general-video
Author or edit a custom HyperFrames composition when no specialized workflow fits, or when BRIEF.md sets flow: companion. Use for longer or multi-scene pieces, brand and sizzle reels, montages, static loops, static title cards, footage remixes, and freeform builds. Use motion-graphics instead for a short unnarrated…
html-ppt-hermes-cyber-terminal
OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.
html-ppt-taste-brutalist
16:9 HTML deck in tactical-telemetry / CRT-terminal taste. Deactivated-CRT charcoal slides, white-phosphor monospace, hazard-red accent, scanline overlay, ASCII syntax, density over decoration. Distilled from Leonxlnx/taste-skill brutalist-skill (Tactical Telemetry mode).
chengfeng-check-updates
An environment manager for a video-editing system. It checks whether its skills and runtime—the software needed to run them—are installed and compatible.
diagnostic-stem-delivery
Audio production with diagnostic analysis, timecode parsing from documents, and verified export workflow.