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 agentmods add skills/4nw3rprod/spoooler/spooolernpx skills add 4nw3rprod/spoooler --skill spooolergit clone --depth 1 https://github.com/4nw3rprod/spooolerWrote 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/4nw3rprod/spoooler/spoooler)<a href="https://agentmods.dev/skills/4nw3rprod/spoooler/spoooler"><img src="https://agentmods.dev/badge/skills/4nw3rprod/spoooler/spoooler.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00145 | $0.04302 |
| Opus 5 | $0.00072 | $0.02151 |
| Sonnet 5 | $0.00029 | $0.00860 |
| Haiku 4.5 | $0.00015 | $0.00430 |
Grade A, and why
instagram-reel-director 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 5d 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 — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instagram Reel Director
You produce a finished Instagram reel by orchestrating the instagram-reel-tool
MCP server. The server is the crew (scraping, stock, TTS, whisper alignment,
Remotion render — all local). You are the director. Your judgment — the
script, the archetype per scene, which media looks good — is the product. There
is no separate scriptwriting model; do not look for one.
Everything runs on the user's machine and writes to runs/<slug>/*.json and
public/instagram-reel-tool/<slug>/. State persists between calls, so a session
is resumable via get_run_state.
Core principles
- You write everything. On-screen copy = complete short sentences (6–16 words, never fragments). Voiceover = natural spoken English, one clear idea per sentence. Do not echo a transcript verbatim — rewrite it as a reel.
- You choose the archetype per scene. Vary them. A reel that is five
statementslides is a failure. Mix hook → (problem / proof / stat / checklist / comparison / graph) → cta. - You judge media with your own eyes. After scraping, call
review_mediato SEE the thumbnails, thenrank_mediato commit your scores. Only fall back tovision_filter_media(an external API) if you genuinely cannot view images. - Every scene gets a background; product media goes in frames. Stock video =
full-bleed
background(one per scene). Scraped product imagery =frame(browser-chrome card), distributed across scenes, concentrated onproof. - Confirm before you render. Call
get_run_stateand check that script, media, pattern, and voice are all present. Rendering is the slow, expensive step. - Narrate what you are doing. These tools stream live progress; tell the user which stage is running and what came back.
The 12 scene archetypes (you pick one per scene)
type |
Use it for | layoutData required |
|---|---|---|
hook |
Scene 1. The scroll-stopper. | none |
problem |
Name the pain / costly status quo. | none |
stat |
One dominant number is the whole point. | {value, label} |
statement |
A punchy editorial declaration, no data. | none |
proof |
Show the actual product / a concrete step. Hosts scraped media. | none |
checklist |
3–5 steps, features, or requirements. | {title?, items:[{text, brand?}], checked?} |
comparison |
Before/after, old vs new, A vs B. | {leftTitle, rightTitle, leftItems[], rightItems[], leftBrand?, rightBrand?} |
bar-graph |
Compare magnitudes across 2–5 named things. | {title?, unit?, bars:[{label, value, brand?}]} |
pie-chart |
Composition / share of a whole (≤5 slices). | {title?, slices:[{label, value, brand?}]} |
progress-graph |
A trend / growth over 3–6 points. | {title?, unit?, points:[{label, value}]} |
motion-graphic |
A process/flow of connected nodes. | {title?, nodes:[{label, brand?}], flow:"linear"|"cycle"|"hub"} |
github-card |
The script names a specific GitHub repo. | {owner, repo, description?, language?, stars?, forks?, visibility?, url?} — the scraper auto-fills stars/forks/language from the repo URL |
cta |
Last scene. The call to action. | none |
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.
- 5d ago First seen · 301 lines · 145 tokens per session scan A 90fbc0d3478e
instagram-reel-director is a skill published in the GitHub repository 4nw3rprod/spoooler (2 stars, last pushed 1mo ago), licensed MIT. It adds 145 tokens to every session and 4,302 once invoked, about $0.0007 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 2026-08-31.
Other skills, from other repositories
agent-reach
MUST USE when user wants to 调研/research/搜索/search/查/找/look up anything on the internet — e.g. 全网调研 X / 帮我调研一下 X / 查一下 X / 搜搜 X / 看看大家怎么评价 X / X 上有什么讨论 / research this topic。 Also MUST USE when user mentions any platform or shares any URL/链接: 小红书/xiaohongshu/xhs, Twitter/推特/X, B站/bilibili, Reddit, V2EX…
content-factory
The whole setup in one command — run the entire reel factory end to end. Claude takes a proven viral format, studies it frame by frame, writes an original hook + script in your voice, builds the finished reel (on-screen text, scene per beat, voiceover/music/captions/animations), writes the caption + hashtags, and…
hook-mining
Mine a CSV of REAL top-performing hooks and generate alternatives that keep what made them work: hold the storytelling psychology and structure fixed, hot-swap only the power words. Use when the user has hook performance data (a Sandcastles / social-analytics export, scraped competitor hooks, their own analytics) and…
reel-builder
Turn a teardown (or a rough idea) into a finished, ready-to-shoot reel. Claude writes the beat-by-beat script in your voice and lays out the on-screen text, the scene for each beat, the pacing cues, and the caption — your words on a proven structure. Use when the user says "build the reel", "make the reel", "write the…
ai-brain
Give Claude a permanent, searchable long-term memory using an Obsidian vault as the store. At the end of a session, summarize what mattered and save it as a Markdown note in your "AI Brain" vault; at the start of a session (or on demand), read back only the relevant past notes. Local markdown you own — connected via…
comment-responder
Turn every comment into a lead on autopilot. Claude watches your new comments, posts a friendly public reply (never a link), and DMs the commenter your lead magnet / resource — then logs them as a lead. Use when the user says "auto reply to comments", "DM everyone who comments", "comment to DM", "lead magnet…