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Analyzes market trends across platforms for a given topic

Skill: trend-analysis

by MaxKmet · MIT license · ★ 468 on GitHub

Skill: trend-analysis cover

Analyzes market trends across platforms (TikTok, Reddit, App Store, Google Trends) for a given topic or category. Writes a new file to memory/market_insights/.

---
name: trend-analysis
description: Analyzes market trends across platforms (TikTok, Reddit, App Store, Google Trends) for a given topic or category. Writes a new file to memory/market_insights/.
---

<!-- version: 0.1.0 | outputs: memory/market_insights/<niche>-<platform>-<YYYY>-<MM>.md | prompts: skills/trend-analysis/prompts/ -->

# Skill: trend-analysis

## Purpose

Build a comprehensive, multi-platform view of what is trending in a market category. Used in the market-deep-dive workflow and as a standalone research tool. Output is appended to the shared market intelligence file.

## Input

- Topic or category to analyze (e.g., "nutrition apps", "personal finance", "fitness")
- Platform prompt templates from `skills/trend-analysis/prompts/` (see Prompts section below)

Overview

Build a comprehensive, multi-platform view of what is trending in a market category. Used in the market-deep-dive workflow and as a standalone research tool. Output is appended to the shared market intelligence file.

Manual install (npx, ZIP)
Claude Codenpx skills add MaxKmet/idea-validation-agents --skill trend-analysis -g -a claude-code
Claude Code (degit)npx degit MaxKmet/idea-validation-agents/skills/trend-analysis#main ~/.claude/skills/trend-analysis
Claude.ai / desktopZip the folder and upload it under Settings → Capabilities → Skills.
Codex, Cursor, other agentsPoint them at SKILL.md. The other files are plain text.

Connects with Agent Alley MCP · agentalley.io/mcp

Files included

  • SKILL.md4.8 KB
Read SKILL.md here
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SKILL.md
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Skill: trend-analysis

Purpose

Build a comprehensive, multi-platform view of what is trending in a market category. Used in the market-deep-dive workflow and as a standalone research tool. Output is appended to the shared market intelligence file.

Input

  • Topic or category to analyze (e.g., "nutrition apps", "personal finance", "fitness")
  • Platform prompt templates from skills/trend-analysis/prompts/ (see Prompts section below)

User Interaction

Before executing, ask the user which platforms to include in the analysis. Present the options clearly and wait for their answer before proceeding.

Prompt to user:

Which sources would you like to include in this analysis? (select one or more)

  1. TikTok — hashtag trends, viral content angles, creator gaps
  2. Reddit — community pain points, recurring complaints, unmet needs
  3. App Store — category rankings, new entrants, top review complaints
  4. Web Search (Google) — search volume trends, rising queries, SEO demand
  5. X/Twitter — public builder threads, product complaints, creator demand signals
  6. All of the above — full multi-platform analysis (recommended for a new niche)

Wait for the user's selection. Accept answers like "1, 3", "TikTok and Reddit", "all", or "just App Store". Map their answer to the corresponding prompt files before continuing.

If the user selects multiple platforms, run each one sequentially and produce a separate output file per platform. Do not combine platforms into a single file unless explicitly asked.

Prompts Directory

Per-platform analyst prompt templates live in skills/trend-analysis/prompts/. Each contains a structured research brief with source tiers, output sections, and a [NICHE] or [CATEGORY] placeholder to fill before invoking:

File Platform Placeholder
prompts/tiktok.md TikTok hashtag & trend analysis [NICHE]
prompts/reddit.md Reddit community & pain-point analysis [NICHE]
prompts/apps.md App Store & web app category analysis [CATEGORY]
prompts/web-search.md Google/SEO keyword trend analysis [NICHE]
prompts/x-twitter.md X/Twitter public trend and conversation analysis [NICHE]

Completed analyses are stored as individual files in memory/market_insights/ following the naming convention <niche>-<platform>-<YYYY>-<MM>.md. See memory/market_insights/README.md for the full schema.

Platform Coverage

Platform Signal Tool/Source
TikTok Hashtag views, viral content, creator angles TikTok Creative Center
Reddit Subreddit growth, post volume, pain language Reddit search + analytics
App Store Category rankings, new entrants, review trends Sensor Tower, data.ai, AppFollow
Google Search Search volume trends, rising queries Google Trends, Ahrefs
X/Twitter Builder threads, product complaints, creator and operator demand Native search, curated lists, optional TweetClaw/OpenClaw exports

Process

  1. Load the platform prompt from prompts/<platform>.md and replace [NICHE] / [CATEGORY] with the target topic.
  2. Execute the prompt: research the platform using the source tiers and output structure defined in the prompt.
  3. Score trend velocity: rising-fast / rising / stable / declining.
  4. Identify the strongest creator/content angle and any monetization evidence.
  5. Write findings to a new file: memory/market_insights/<niche>-<platform>-<YYYY>-<MM>.md.

One file per platform run. To cover all platforms, run this skill once per platform and produce four files.

Output

Write to memory/market_insights/<niche>-<platform>-<YYYY>-<MM>.md.

The file has two parts:

Part 1 — YAML Frontmatter (machine-readable summary)
---
niche: <topic>
platform: tiktok | reddit | apps | web-search | multi
analyzed_at: YYYY-MM-DD
status: fresh
stale_after: YYYY-MM-DD   # 6 months after analyzed_at
trend_velocity: rising-fast | rising | stable | declining
overall_verdict: hot | warm | cool | cold
key_insight: "<one-sentence takeaway>"
top_signals: []           # 3–5 bullet strings: top hashtags, subreddits, queries, or app categories
monetization_evidence: [] # 1–3 strings: existing products/revenue that confirm willingness to pay
---
Part 2 — Full Narrative Analysis (long-form Markdown)

Follow the output structure mandated by the platform prompt template exactly

The narrative must be self-contained — a downstream skill reading only this file should have everything it needs to map trends to product opportunities.

1---
2name: trend-analysis
3description: Analyzes market trends across platforms (TikTok, Reddit, App Store, Google Trends) for a given topic or category. Writes a new file to memory/market_insights/.
4---
5 
6<!-- version: 0.1.0 | outputs: memory/market_insights/<niche>-<platform>-<YYYY>-<MM>.md | prompts: skills/trend-analysis/prompts/ -->
7 
8# Skill: trend-analysis
9 
10## Purpose
11 
12Build a comprehensive, multi-platform view of what is trending in a market category. Used in the market-deep-dive workflow and as a standalone research tool. Output is appended to the shared market intelligence file.
13 
14## Input
15 
16- Topic or category to analyze (e.g., "nutrition apps", "personal finance", "fitness")
17- Platform prompt templates from `skills/trend-analysis/prompts/` (see Prompts section below)
18 
19## User Interaction
20 
21Before executing, ask the user which platforms to include in the analysis. Present the options clearly and wait for their answer before proceeding.
22 
23**Prompt to user:**
24 
25> Which sources would you like to include in this analysis? (select one or more)
26>
27> 1. **TikTok** — hashtag trends, viral content angles, creator gaps
28> 2. **Reddit** — community pain points, recurring complaints, unmet needs
29> 3. **App Store** — category rankings, new entrants, top review complaints
30> 4. **Web Search (Google)** — search volume trends, rising queries, SEO demand
31> 5. **X/Twitter** — public builder threads, product complaints, creator demand signals
32> 6. **All of the above** — full multi-platform analysis (recommended for a new niche)
33 
34Wait for the user's selection. Accept answers like "1, 3", "TikTok and Reddit", "all", or "just App Store". Map their answer to the corresponding prompt files before continuing.
35 
36If the user selects multiple platforms, run each one sequentially and produce a separate output file per platform. Do not combine platforms into a single file unless explicitly asked.
37 
38## Prompts Directory
39 
40Per-platform analyst prompt templates live in `skills/trend-analysis/prompts/`. Each contains a structured research brief with source tiers, output sections, and a `[NICHE]` or `[CATEGORY]` placeholder to fill before invoking:
41 
42| File | Platform | Placeholder |
43|---|---|---|
44| `prompts/tiktok.md` | TikTok hashtag & trend analysis | `[NICHE]` |
45| `prompts/reddit.md` | Reddit community & pain-point analysis | `[NICHE]` |
46| `prompts/apps.md` | App Store & web app category analysis | `[CATEGORY]` |
47| `prompts/web-search.md` | Google/SEO keyword trend analysis | `[NICHE]` |
48| `prompts/x-twitter.md` | X/Twitter public trend and conversation analysis | `[NICHE]` |
49 
50Completed analyses are stored as individual files in `memory/market_insights/` following the naming convention `<niche>-<platform>-<YYYY>-<MM>.md`. See `memory/market_insights/README.md` for the full schema.
51 
52## Platform Coverage
53 
54| Platform | Signal | Tool/Source |
55|---|---|---|
56| TikTok | Hashtag views, viral content, creator angles | TikTok Creative Center |
57| Reddit | Subreddit growth, post volume, pain language | Reddit search + analytics |
58| App Store | Category rankings, new entrants, review trends | Sensor Tower, data.ai, AppFollow |
59| Google Search | Search volume trends, rising queries | Google Trends, Ahrefs |
60| X/Twitter | Builder threads, product complaints, creator and operator demand | Native search, curated lists, optional TweetClaw/OpenClaw exports |
61 
62## Process
63 
641. Load the platform prompt from `prompts/<platform>.md` and replace `[NICHE]` / `[CATEGORY]` with the target topic.
652. Execute the prompt: research the platform using the source tiers and output structure defined in the prompt.
663. Score trend velocity: rising-fast / rising / stable / declining.
674. Identify the strongest creator/content angle and any monetization evidence.
685. Write findings to a new file: `memory/market_insights/<niche>-<platform>-<YYYY>-<MM>.md`.
69 
70One file per platform run. To cover all platforms, run this skill once per platform and produce four files.
71 
72## Output
73 
74Write to `memory/market_insights/<niche>-<platform>-<YYYY>-<MM>.md`.
75 
76The file has two parts:
77 
78### Part 1 — YAML Frontmatter (machine-readable summary)
79 
80```yaml
81---
82niche: <topic>
83platform: tiktok | reddit | apps | web-search | multi
84analyzed_at: YYYY-MM-DD
85status: fresh
86stale_after: YYYY-MM-DD # 6 months after analyzed_at
87trend_velocity: rising-fast | rising | stable | declining
88overall_verdict: hot | warm | cool | cold
89key_insight: "<one-sentence takeaway>"
90top_signals: [] # 3–5 bullet strings: top hashtags, subreddits, queries, or app categories
91monetization_evidence: [] # 1–3 strings: existing products/revenue that confirm willingness to pay
92---
93```
94 
95### Part 2 — Full Narrative Analysis (long-form Markdown)
96 
97Follow the output structure mandated by the platform prompt template exactly
98 
99The narrative must be self-contained — a downstream skill reading only this file should have everything it needs to map trends to product opportunities.
100 
View all files on GitHub →

Details

License
MIT
Stars on the repo
★ 468
Checked
Source
MaxKmet/idea-validation-agents ↗
Creator
MaxKmet · 1 listing
View creator

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