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 Pika-Labs/Pika-Plugins --skill fix-my-lookgit clone --depth 1 https://github.com/Pika-Labs/Pika-PluginsWrote 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/pika-labs/pika-plugins/fix-my-look)<a href="https://agentmods.dev/skills/pika-labs/pika-plugins/fix-my-look"><img src="https://agentmods.dev/badge/skills/pika-labs/pika-plugins/fix-my-look/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/pika-labs/pika-plugins/fix-my-look"><img src="https://agentmods.dev/badge/skills/pika-labs/pika-plugins/fix-my-look.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
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 | $0.00161 | $0.02872 |
| Opus 5 | $0.00081 | $0.01436 |
| Sonnet 5 | $0.00032 | $0.00574 |
| Haiku 4.5 | $0.00016 | $0.00287 |
Grade A, and why
fix-my-look 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 10d 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 — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
fix-my-look
Edit the source's first usable frame with gpt-image-2 from the user's prompt,
then propagate that look across the clip with kling reference-video while
locking the original face, motion and audio via the original video + audio as
references. All prep happens in one normalize_video
call for short clips, or one normalize call per segment for longer clips. The
output ratio uses the normalized clip's closest supported output ratio; this
skill does NOT reframe the source video.
Inputs
<source>— path or URL to a video file with audio<change_prompt>— what to change (e.g. "make it night with neon lights", "change my shirt to a leather jacket", "put me on a beach in Hawaii")
Empty-args menu
- "What's the source video path?"
- "What do you want to change? (e.g. 'put me on a beach', 'make it night')"
Workflow
Working dir: ~/Downloads/fix-my-look/<run-id>/.
Step 0 — Cost, timer and task IDs
Every tool named below is a Pika MCP tool, written by its bare name. Call it under whatever prefix your session exposes for the Pika MCP.
Start a timer when the source and change prompt are known. Before paid
generation, call estimate_cost for the planned
generate_image_edit,
generate_reference_video, any multi-segment
edit_concat, and any optional audio/lipsync repair
call. If cost is not surfaced by the host, say
Cost not surfaced by this harness in the final report instead of guessing.
When any tool returns a
task_id, copy the exact value into the run notes and reuse it verbatim; do not
hand-type long JWT-style task IDs.
Step 1 — Prepare the clip
Local file? upload_asset it first; an HTTPS media URL
passes directly. Decide the source windows before normalizing: use one 14.8s
window for sources <=15s, and split longer sources into ordered 14.8s windows.
Call
normalize_video(video_url=<source>, start_s=<offset>, max_duration_s=14.8, extract_audio=true, extract_face_frame=true)
once per window. Use the first window's face_frame_url for the edited still;
use each window's video_url as that segment's motion/identity reference. For
multi-window clips, also call
extract_audio_from_video(video_url=<source>) so the
final merged output can be restored to one continuous source audio track.
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.
- 10d ago First seen · 218 lines · 161 tokens per session scan A 51ffcbbbeb3a
fix-my-look is a skill published in the GitHub repository Pika-Labs/Pika-Plugins (40 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 161 tokens to every session and 2,872 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).
diagnostic-stem-delivery
Audio production with diagnostic analysis, timecode parsing from documents, and verified export workflow.
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.