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Setup

skill-devinilabs-content-research-os-setup · by devinilabs

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Install

$ agentstack add skill-devinilabs-content-research-os-setup

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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no reviews yet
2mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

Setup — Content Research OS

Conversational onboarding. Interview the user, then write their configuration. Be warm, brief, and clear. Ask one topic at a time and let the user skip anything — never block on a single answer.

Before you start

  1. Detect fresh setup vs. re-run: read .env (if present) and the four files in .claude/context/.
  • If real values already exist (a key counts as configured only if it's non-blank and not a your-..-here placeholder; an account only if it's not @example), summarize what's already configured and ask whether to update specific parts or start fresh. When updating, change only what the user asks for — never clobber existing API keys or accounts they didn't mention.
  1. Briefly tell the user what you'll collect: three API keys, their YouTube channel details, and the X / Instagram / TikTok accounts to track.

Group A — API keys

Ask for each key on its own line of conversation. For each, give the one-line "where to get it" link and offer "skip for now" (you'll leave that key blank in .env, and note the matching skill won't run until it's filled).

| Key | Powers | Get it from | |-----|--------|-------------| | APIFY_TOKEN | X, Instagram, TikTok scraping | https://console.apify.com/account/integrations | | TUBELAB_API_KEY | YouTube outlier detection | https://tubelab.net/settings/api | | GEMINI_API_KEY | AI video analysis | https://aistudio.google.com/apikey |

Group B — Your YouTube channel

Channel URL/@handle is required; everything else is optional but improves relevance filtering.

  • Channel URL or @handle
  • Channel ID (24 chars, starts with UC…). If the user doesn't know it, try to resolve it from the handle by fetching the channel page and reading the UC… id; if you can't, ask them to paste it from YouTube Studio → Settings → Channel → Advanced, or store UC_REPLACE_ME and tell them youtube-research needs it.
  • Channel name
  • Primary niche
  • Content style (e.g., tutorials, vlogs, reviews)
  • Target audience
  • Typical video length
  • Upload frequency
  • Best-performing topics
  • Goals

Group C — Accounts to track

For X, then Instagram, then TikTok, ask which accounts to research. Let the user paste a list in any format (commas or new lines, with or without @). Optionally capture a niche and a note per handle. If a platform has none, leave its table empty.

Writing the files

When the interview is done, echo a summary first with API keys masked (show only the first 6 and last 2 characters, e.g. apify_a1b2…z9). Then write the files exactly as specified below.

.env

Write all three keys. Use the user's value, or leave the value blank if skipped — a blank makes the matching script report a clean "not set" error instead of a confusing auth failure. Preserve any extra keys the user already had.

# YouTube Research - TubeLab API
TUBELAB_API_KEY=

# X/Twitter, Instagram, TikTok Research - Apify API
APIFY_TOKEN=

# Video Analysis - Gemini API
GEMINI_API_KEY=

.claude/context/x-accounts.md, instagram-accounts.md, tiktok-accounts.md

Strict format — the fetch scripts parse these. For all three: the header row MUST start with | Handle, the separator MUST start with |--- (no space after the first pipe), and each handle goes in the second column with a leading @. Never write an @example row — replace the placeholder with real handles. If a platform has no accounts, write only the header + separator.

X (.claude/context/x-accounts.md):

# X/Twitter Accounts to Track

Add accounts below to track for research. The fetch script will pull content from these accounts.

| Handle | Niche | Notes |
|--------|-------|-------|
| @handle1 | niche | notes |

Use the same structure for Instagram (title # Instagram Accounts to Track) and TikTok (title # TikTok Accounts to Track).

.claude/context/youtube-channel.md

Keep this exact section structure — youtube-research reads Channel ID and Primary Niche from here:

# YouTube Channel Context

## Channel Information
- **Channel Name:** 
- **Channel Handle:** 
- **Channel ID:** 

## Niche & Positioning
- **Primary Niche:** 
- **Content Style:** 
- **Target Audience:** 

## Content Strategy
- **Typical Video Length:** 
- **Upload Frequency:** 
- **Best Performing Topics:** 

## Goals
- **Growth Targets:** 
- **Content Goals:** 

Finish

Tell the user:

  • What was written, and which keys were left blank (so they know which skills won't run until those are filled).
  • If the channel ID is UC_REPLACE_ME, remind them youtube-research needs it.
  • Next steps: in Claude Desktop, upload the .skill bundles (Settings → Capabilities → Skills) if not done, then run /content-planner for a full cross-platform pass, or an individual skill like /x-research.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.