# Hooklayer

> Hooklayer — khan-ashifur-hooklayer. Use this tool when you need to analyze and replicate the success of TikTok creators, and optimize your content for virality. Hooklayer provides real-time performance data, viral DNA scoring, and automated tools to help you identify top-performing content, predict virality, and generate high-quality scripts. With a simple interface and automated tool chaining, Hooklayer solves problems in content creation, social media marketing, and influencer research, taking in TikTok handles, URLs, or transcripts and outputting actionable insights and optimized content.

Canonical page: https://skillsregistry.net/skills/khan-ashifur-hooklayer  
JSON: https://api.skillsregistry.net/v1/skills/khan-ashifur-hooklayer

## Description

**Live TikTok creator intelligence for AI agents.**

Hooklayer pulls real performance data from any TikTok handle in seconds: viral DNA scoring, replicability analysis, top-performing video breakdowns, format fingerprints, hook patterns, and a stealable steal_map.

**7 MCP tools that chain automatically:**

- **analyze_account** (5 credits) — TikTok creator deep dive. Returns viral_dna, steal_map, format_fingerprint, top 5 videos, content_gaps, and a `recommended_chain` field that pre-fills the next 3 tool calls. **The agentic anchor.**
- **score_hook** (1 credit) — Score any hook 0-100 against proven viral patterns. Returns 3 rewrites at higher quality.
- **viral_remix** (3 credits) — URL or transcript → fresh scene-by-scene script with mirrored viral DNA.
- **trend_pulse** (1 credit) — Rising opportunities + saturated patterns per niche.
- **find_viral_template** (1 credit) — Niche-fit ranked templates with hook patterns and example URLs.
- **match_voice** (2 credits) — Extract a creator's voice DNA, rewrite a draft in their style.
- **predict_virality** (2 credits) — Score a draft script for viral potential before publishing.

**The agentic chain pattern:** call `analyze_account` once → agent reads `recommended_chain` → fires the next 3 tools with params pre-filled. No prompt engineering, no glue code.

**Auth:** Bearer (`hl_live_*`) OR OAuth 2.1 + PKCE + Dynamic Client Registration. RFC 8414, 9728, 7591, 6750, 7636 compliant.

**Free tier:** 100 lifetime credits, no card required. Mint instantly at https://hooklayer.dev/auth/signup

**Paid tiers:** $49 Starter / $149 Pro (most popular) / $499 Agency. 20% annual discount.

Listed on the [Anthropic Official MCP Registry](https://registry.modelcontextprotocol.io) as `io.github.khan-ashifur/hooklayer` v1.0.0.

**Docs:** https://hooklayer.dev/docs
**Playground:** https://hooklayer.dev/playground
**GitHub:** https://github.com/khan-ashifur/hooklayer

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** version-control
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/khan-ashifur/hooklayer)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "khan-ashifur-hooklayer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/khan-ashifur-hooklayer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/khan-ashifur-hooklayer/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt