Generative-Media-Skills is a toolkit that lets AI agents generate, edit, and display images, videos, and audio through the muapi command-line interface. It is for users of Claude Code, Cursor, Gemini CLI, and OpenCode who need multimodal media-generation workflows. The catalogue entries are the skills that expose these media capabilities to coding agents.
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 SamurAIGPT/Generative-Media-Skills --skill muapi-instagram-postgit clone --depth 1 https://github.com/SamurAIGPT/Generative-Media-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/samuraigpt/generative-media-skills/muapi-instagram-post)<a href="https://agentmods.dev/skills/samuraigpt/generative-media-skills/muapi-instagram-post"><img src="https://agentmods.dev/badge/skills/samuraigpt/generative-media-skills/muapi-instagram-post/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/samuraigpt/generative-media-skills/muapi-instagram-post"><img src="https://agentmods.dev/badge/skills/samuraigpt/generative-media-skills/muapi-instagram-post.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 57 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 57 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00026 | $0.00705 |
| Opus 5.5 | $0.00010 | $0.00282 |
| Sonnet 5.5 | $0.00005 | $0.00141 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade B, and why
muapi-instagram-post scanned grade B with 2 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 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
- For model IDs without a CLI alias yet, fall back to the raw endpoint via `curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}'` and poll with Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- For model IDs without a CLI alias yet, fall back to the raw endpoint via `curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}'` and poll with Copies of this mod
1 near-identical copy found in the catalogue:
- muapi-instagram-post — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instagram Post
Create a polished, on-brand Instagram post — square or portrait hero image with matching caption and hashtags.
Inputs
| Name | Type | Required | Default | Description |
|---|---|---|---|---|
brief |
text | yes | — | What the post is about (e.g. "summer coffee launch at our café, warm golden vibes"). |
brand_style |
text | no | modern, vibrant, clean typography, lifestyle photography aesthetic | Brand personality and visual style tags. |
format |
text | no | 1:1 | Post format — "1:1" for feed square, "4:5" for portrait feed, "9:16" for Reels. |
Steps
This skill produces one polished Instagram-ready visual + caption. Use the plan if generating more than one variant.
Phase A — Generate the hero image
- Write a detailed, atmosphere-rich image prompt based on
{{brief}}and{{brand_style}}:- Include lighting direction, color palette, mood, subject placement, and lens feel.
- Optimize for Instagram aesthetics: clean, punchy, single focal point.
- Append style tags:
{{brand_style}}, social media photography, highly detailed.
- Call
muapi image generate(model=nano-banana-2, aspect_ratio={{format}}). - If the user provided a product or subject image in the session, prefer
muapi image editinstead to maintain visual consistency.
Phase B — Caption & Hashtags
After the image is generated, compose and return:
- Caption: 2–4 lines. Hook line first (punchy, curiosity-driving), then brand message, then CTA.
- Hashtags: 15–20 targeted hashtags (mix of niche, mid-tier, and broad). Format as a separate block.
Notes
- Prioritize scroll-stopping first impressions — the image must visually communicate the brief within 2 seconds.
- If
formatis9:16(Reels cover), note that text overlays are common; include a suggestion for on-screen text placement. - Do NOT generate multiple variants unless the user explicitly asks.
Trigger Keywords
instagram post, ig post, instagram, feed post, instagram creative
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 First seen · 59 lines · 26 tokens per session scan B 70b2dd07fada
muapi-instagram-post is a skill published in the GitHub repository SamurAIGPT/Generative-Media-Skills (25 stars, last pushed 28d ago), licensed MIT. It adds 26 tokens to every session and 705 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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mlops-validation
Add the validation layers that gate a merge — ty typing, Ruff linting, pytest coverage, structured logging, and the trivy, pip-audit, and gitleaks scans. Use when hardening code quality or wiring the mise run check task.
mlops-prototyping
Structure reproducible Jupyter notebooks with a fixed section layout, hoisted configuration, and leakage-free scikit-learn pipelines. Use when exploring a dataset, training a first model, or preparing a notebook for promotion.
mlops-observability
Make an ML system a glass box with reproducible runs, MLflow dataset lineage, drift monitoring, alerting, and SHAP explanations. Use when a deployed model needs traceability, monitoring, alerting, or explanation.
mlops-collaboration
Prepare a project for public collaboration — license, code of conduct, docs, branch rulesets, templates, and git-cliff releases. Use when open-sourcing a repository, onboarding contributors, or cutting a tagged release.
mlops-industrialization
Convert notebook prototypes into a distributable Python package with a src layout, a domain/io/application split, and validated OmegaConf plus Pydantic configuration. Use when moving code out of notebooks or designing entrypoints.