gameday

gameday is a skill for Claude Code from Pika-Labs/Pika-Plugins. It costs 103 tokens per session (1,477 once invoked), scanned A, original, Apache-2.0.

A workflow for turning one user photo and a favorite sports team into six separate matchday fan photos. The person remains the same across the generated images while the scenes show different game-day moments.

In plain words
What is it for?
Use it to create a six-image sports-fan carousel showing the person at a game in their team's colors.
Why use it?
It provides a consistent set of fan images for a carousel without requiring six separate photos from the user.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the pika plugin — 20 skills, 1 MCP server shipped together

not rated 40repo 1mo ago A scan Socket: passSnyk: passSkillSpector: pass 103 tokens original Apache-2.0

Good fit Use it to create a six-image sports-fan carousel showing the person at a game in their team's colors.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pika-labs/pika-plugins/gameday
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.

Any agent
npx skills add Pika-Labs/Pika-Plugins --skill gameday
Clone the repo
git clone --depth 1 https://github.com/Pika-Labs/Pika-Plugins

Made for: Claude Code.

Or install pika, the plugin that ships this one along with the rest of its 20 skills, 1 MCP server.

Wrote 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.

agentmods badge for gameday

README.md
[![agentmods](https://agentmods.dev/badge/skills/pika-labs/pika-plugins/gameday/github.svg)](https://agentmods.dev/skills/pika-labs/pika-plugins/gameday)
Your own site
<a href="https://agentmods.dev/skills/pika-labs/pika-plugins/gameday"><img src="https://agentmods.dev/badge/skills/pika-labs/pika-plugins/gameday/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.

agentmods 80×15 button for gameday

Your own site · 80×15
<a href="https://agentmods.dev/skills/pika-labs/pika-plugins/gameday"><img src="https://agentmods.dev/badge/skills/pika-labs/pika-plugins/gameday.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 103 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,477 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 21 Jul 2026
  • Snyk pass 21 Jul 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found 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 5.1 $0.00103 $0.01477
Opus 5 $0.00051 $0.00739
Sonnet 5 $0.00021 $0.00295
Haiku 4.5 $0.00010 $0.00148

Measured 9d ago against content hash dabc06170709, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

gameday 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 9d 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.

skills/gameday/SKILL.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

gameday

The user uploads one photo of themselves and gives their favorite team. You generate 6 separate photos of that person as a superfan at the game — a matchday carousel.

Steps

  1. Get the two inputs. Photo (local path or URL) and favorite team. If the photo is a local path, upload it (upload_asset → PUT to presigned_url → use public_url). Call the resulting URL photo.

  2. Fill the team. From the team name, fill {team} and {kit colors} (two main colors + stripe pattern, e.g. Argentina → "sky-blue and white vertical stripes"). Describe colors, not crests/logos.

  3. Generate the 6 photos. Make 6 separate generate_image_edit calls, one per prompt below, passing the same photo as images on every call (this keeps the face identical). Settings each call: provider: gpt-image-2, images: [photo], aspect_ratio: 3:4, quality: medium, output_format: png.

  4. Deliver the 6 separate images in order. Six files — never one image split into panels.

The 6 prompts (substitute {team} / {kit colors})

p1 — Arrival at the stadium

Ultra-realistic candid lifestyle sports-fan photograph, single vertical phone photo, 3:4. The
subject is the SAME person as the reference photo — preserve their exact face, hair, features,
skin tone and vibe; natural candid expression. A passionate {team} football supporter arriving on
match day, wearing an official {team} home jersey ({kit colors}) with a matching {kit colors}
{team} supporter scarf looped around the neck, effortless game-day styling. They walk confidently
toward a big modern stadium's entrance gates, golden late-afternoon sun flaring low behind the
stands, long warm shadows. Streams of other fans in the same {kit colors} flow around them,
flags and team colors everywhere, a buzzing pre-match crowd. Candid street-style framing, slight
motion in the step, shallow depth of field on the background, realistic smartphone photo look,
authentic and unposed.

p2 — In the seats before kickoff

Ultra-realistic candid lifestyle sports-fan photograph, single vertical phone photo, 3:4. The
subject is the SAME person as the reference photo — preserve their exact face, hair, features,
skin tone and vibe. A {team} supporter in an official {team} jersey ({kit colors}) and matching
{team} scarf, sitting in the stadium seats before kickoff, leaning casually on the armrest, looking
thoughtfully out toward the green pitch. Behind them a massive blurred crowd fills the stands,
a sea of {kit colors}, the floodlights and tiered stadium bowl rising up. Soft natural daylight,
candid quiet-before-the-storm mood, gentle bokeh on the crowd, realistic smartphone photo look,
authentic and unposed.

Read the full file on GitHub · 102 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. 9d ago First seen · 102 lines · 103 tokens per session scan A dabc06170709

Subscribe to this mod's changes

gameday is a skill published in the GitHub repository Pika-Labs/Pika-Plugins (40 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 103 tokens to every session and 1,477 once invoked, about $0.0005 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.

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