Viral Short Form Ideas
vyralcontent/content-skills
Generate short-form video ideas at volume and stop the blank-page problem for good.
Maps viral social content and trending topics to concrete app opportunities by extracting the underlying problem and validating monetization fit.
Install Trend To Product Mapper
$ npx skills add MaxKmet/idea-validation-agents --skill trend-to-product-mapper -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install MaxKmet/idea-validation-agents trend-to-product-mapper --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/trend-to-product-mapper .claude/skills/trend-to-product-mapper && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "trend-to-product-mapper" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/trend-to-product-mapper into .claude/skills/trend-to-product-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trend-to-product-mapper", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/trend-to-product-mapperType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add MaxKmet/idea-validation-agents --skill trend-to-product-mapper -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install MaxKmet/idea-validation-agents trend-to-product-mapper --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/trend-to-product-mapper .agents/skills/trend-to-product-mapper && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "trend-to-product-mapper" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/trend-to-product-mapper into .agents/skills/trend-to-product-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trend-to-product-mapper", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MaxKmet/idea-validation-agents --skill trend-to-product-mapper -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install MaxKmet/idea-validation-agents trend-to-product-mapper --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/trend-to-product-mapper .cursor/skills/trend-to-product-mapper && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "trend-to-product-mapper" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/trend-to-product-mapper into .cursor/skills/trend-to-product-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trend-to-product-mapper", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/MaxKmet/idea-validation-agents.git --path skills/trend-to-product-mapper--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add MaxKmet/idea-validation-agents --skill trend-to-product-mapper -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install MaxKmet/idea-validation-agents trend-to-product-mapper --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/trend-to-product-mapper .gemini/skills/trend-to-product-mapper && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "trend-to-product-mapper" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/trend-to-product-mapper into .gemini/skills/trend-to-product-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trend-to-product-mapper", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install MaxKmet/idea-validation-agents trend-to-product-mapperInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add MaxKmet/idea-validation-agents --skill trend-to-product-mapper -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/trend-to-product-mapper .github/skills/trend-to-product-mapper && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "trend-to-product-mapper" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/trend-to-product-mapper into .github/skills/trend-to-product-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trend-to-product-mapper", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MaxKmet/idea-validation-agents --skill trend-to-product-mapper -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install MaxKmet/idea-validation-agents trend-to-product-mapper --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/trend-to-product-mapper .opencode/skills/trend-to-product-mapper && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "trend-to-product-mapper" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/trend-to-product-mapper into .opencode/skills/trend-to-product-mapper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "trend-to-product-mapper", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
trend-to-product-mapper- GitHub stars
- 478
- Token cost
- ~1.8k tokens
- SKILL.md length
- 526 words
- Files
- 1
- Skills in repo
- 15
- Repo updated
- First seen
- Licence
- MIT
At a glance
Maps viral social content and trending topics to concrete app opportunities by extracting the underlying problem and validating monetization fit.
- Works in 3 steps: memory/market_insights/ — list any… → memory/user_profile.md — check for… → The current conversation — did the user…
- Tasks that involve Social media posts
- SKILL.md covers Purpose, User Interaction, Input and Pipeline, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Trend To Product Mapper is an agent skill from MaxKmet/idea-validation-agents. Maps viral social content and trending topics to concrete app opportunities by extracting the underlying problem and validating monetization fit.
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Productivity & Automation, covering Social media posts, Health and fitness tracking and Brainstorming. It works with TikTok. The repository describes itself as: AI agents that act as your personal venture analyst - from startup idea brainstorming to full validation and go-to-market strategy. Built for developers who'd rather validate in… The licence is MIT.
When your agent uses it
- Tasks that involve Social media posts
- Tasks that involve Health and fitness tracking
- Tasks that involve Brainstorming
Example prompts
- “/trend-to-product-mapper”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- memory/market_insights/ — list any existing trend-analysis files; extract niche names from filenames (e.g., nutrition-tiktok-2026-04.md →…
- memory/user_profile.md — check for domain, interests, or background fields
- The current conversation — did the user mention a topic or market earlier?
What it can do on your machine
Read from SKILL.md and the folder at commit 3a4c800. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml and markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Trend To Product Mapper loads about 1.8k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 526 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from MaxKmet/idea-validation-agents at commit 3a4c800, republished under its MIT licence (© MaxKmet). 526 words, ~1,778 tokens.
Download SKILL.mdSave it as
.claude/skills/trend-to-product-mapper/SKILL.md (or your agent's skills folder).- name
- trend-to-product-mapper
- description
- Maps viral social content and trending topics to concrete app opportunities by extracting the underlying problem and validating monetization fit.
<!-- version: 0.3.0 | outputs: memory/ideas/<slug>/idea.md (up to 10 per run) -->Skill: trend-to-product-mapper
Purpose
Surface app ideas from real-world signals rather than speculation. The pipeline is: viral content → extract problem → map to app → validate monetization. This skill bridges social listening and product ideation.
User Interaction
Before executing, clarify which niche to analyze. Use available context to suggest options — don't ask blindly.
Step 1 — Infer candidates from context:
Check in this order:
memory/market_insights/— list any existing trend-analysis files; extract niche names from filenames (e.g.,nutrition-tiktok-2026-04.md→ "nutrition")memory/user_profile.md— check fordomain,interests, orbackgroundfields- The current conversation — did the user mention a topic or market earlier?
Step 2 — Present options:
If candidates were found from context:
Which niche would you like to map to a product opportunity?
Based on available research:
- [inferred niche] (trend data: [platform] [period])
- [other inferred niches if any]
Or describe your own — e.g., "productivity tools for freelancers", "pet care", "language learning"
If no candidates were found:
What niche or market category would you like to explore? A few starting points:
- Fitness / nutrition / weight loss
- Personal finance / investing
- Mental health / mindfulness
- Productivity / focus
- Or describe your own in a few words
Step 3 — Confirm:
Once the user selects or describes a niche, confirm it back and proceed to Process.
Input
- Target niche (e.g., "nutrition", "fitness", "personal finance")
memory/market_insights/<niche>-<platform>-<YYYY>-<MM>.md— one or more trend-analysis output files for the niche. Read the full narrative (Part 2) from each file; do not rely solely on the YAML frontmatter.memory/user_profile.mdto filter for user's domain fit and constraints
Pipeline
trend-analysis output → scan for distinct opportunities → extract problem per opportunity → validate monetization → write up to 10 idea.md filesWhat to Read from Trend-Analysis Output
| Section in trend-analysis file | What to extract |
|---|---|
| Emerging / Rising Trends | Fastest-moving problems and content angles |
| Financial Opportunities | Willingness-to-pay evidence and market size estimates |
| Key Hashtags / Subreddits / Keyword Clusters | Vocabulary the audience uses for the problem |
| Strategic Insights | Creator gaps and underserved segments |
monetization_evidence (YAML frontmatter) | Quick-scan: is anyone already paying? |
Prefer signals that appear across multiple platforms — cross-platform resonance is a stronger product signal than single-platform virality.
Show full SKILL.md (219 more words)Show less
Process
- Read available trend-analysis files relevant for the niche from
memory/market_insights/. - Scan the full narrative of each file and identify distinct product opportunities — different underlying problems, different audience segments, or different app categories count as distinct. Do not list variations of the same idea.
- Rank candidates by signal strength: weight cross-platform resonance and willingness-to-pay evidence most heavily. Drop candidates with no monetization signal.
- Take the top 5–10 candidates (only include as many as have genuine signal — do not pad to reach 10).
- For each candidate: extract the underlying problem (frustration or desire, not content topic), emotional trigger, audience vocabulary, app category, key features, key differentiator, and monetization evidence.
- Assign a slug to each idea (kebab-case, max 40 chars, derived from the app concept).
- Write one
idea.mdper idea to its own directory:memory/ideas/<slug>/idea.md.
Output
For each identified opportunity, write to memory/ideas/<slug>/idea.md.
The file uses YAML frontmatter for machine-readable metadata and a full narrative body for human readability and downstream skill consumption.
Frontmatter
---
idea_slug: <slug>
status: candidate
created_at: <ISO date>
source_niche: <niche>
source_files: [] # memory/market_insights/ filenames read
platforms_covered: [] # e.g. ["tiktok", "reddit"]
trend_velocity: rising-fast | rising | stable | declining
cross_platform_resonance: true | false
monetization_validated: true | false
confidence: high | medium | low
---Body
Write the following sections in full prose or structured lists — no abbreviation:
# <App Concept Name>
## The Problem
What specific frustration or unmet desire is this idea addressing? Describe it from the user's perspective — the emotional experience, not the feature gap. Include the exact vocabulary the audience uses.
**Emotional trigger:** <the core feeling driving the behavior — anxiety, FOMO, shame, aspiration, etc.>
**Audience vocabulary:** <3–5 exact phrases pulled from hashtags, post titles, or search queries>
## Market Signal Evidence
What trend data supports this? For each platform covered, cite the specific signal:
- **TikTok:** <hashtag, view count, content angle>
- **Reddit:** <subreddit, recurring post type, upvote pattern>
- **App Store:** <category trend, review complaint pattern, new entrant activity>
- **Web Search:** <rising query, search volume indicator>
**Trend velocity:** <rising-fast | rising | stable | declining>
**Cross-platform resonance:** <yes/no — does the same problem appear on 2+ platforms?>
## App Concept
What is the app? Describe it in 2–3 sentences as if pitching to a user, not an investor. Focus on what it does and who it's for.
**App category:** <e.g., habit tracker, AI coach, marketplace, tool>
## Key Features
The 3–5 core features that directly address the problem. Each feature should map to a specific pain point or desire from the Market Signal Evidence section.
1. **<Feature name>** — <what it does and why it matters>
2. ...
## Key Differentiator
What makes this meaningfully different from what already exists? Reference the saturation assessment from the trend-analysis Financial Opportunities section. One clear wedge — not a feature list.
## Monetization Evidence
What proof exists that people pay for solutions to this problem?
- <existing product / revenue signal / pricing evidence>
- ...
**Monetization validated:** <yes/no>
## Confidence Assessment
**Overall confidence:** <high | medium | low>
Reasoning: <1–2 sentences explaining the confidence level — what's strong, what's uncertain>After writing all files, present a summary table to the user:
| # | Slug | App Concept | Confidence | Cross-Platform | Monetization |
|---|---|---|---|---|---|
| 1 | <slug> | ... | high/medium/low | yes/no | validated/unvalidated |
| ... |
Notes
<!-- TODO: Define what counts as "monetization validated" — IH revenue post? App Store paid app? -->© MaxKmet, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/trend-to-product-mapper of MaxKmet/idea-validation-agents.
Open the folder on GitHubat commit 3a4c800
Compare with similar skills
Trend To Product Mapper next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Trend To Product Mapper this skillMaxKmet/idea-validation-agents | 478 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Viral Short Form Ideasvyralcontent/content-skills | 134 | 1 repos | ~2.9k | Automated safety check: Pass | MIT | |
| Content CoachBlotato-Inc/blotato-skills | 183 | — | ~1.8k | Automated safety check: Pass | None | |
| Brainstorm Linkedintechwolf-ai/ai-first-toolkit | 132 | — | ~554 | Automated safety check: Pass | MIT | |
| Trendwatchnestyme/awesome-prompts | 151 | — | ~10k | Automated safety check: Pass | None | |
| Brainstorm Opiniontechwolf-ai/ai-first-toolkit | 132 | — | ~354 | Automated safety check: Pass | MIT |
Similar skills
Content Coach
Blotato-Inc/blotato-skills
Guides a beginner marketer end-to-end from "I don't know what to post" to a scheduled social post.
Brainstorm Linkedin
techwolf-ai/ai-first-toolkit
Generate LinkedIn post ideas from external sources (files, URLs, research).
Trendwatch
nestyme/awesome-prompts
Reverse-engineer viral organic TikTok/Instagram content from competitor accounts and generate adapted hook ideas for the user's app.
Brainstorm Opinion
techwolf-ai/ai-first-toolkit
Generate opinion piece ideas from recent LinkedIn posts (last 30 days).
Social
coreyhaines31/marketingskills
When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, or Facebook, or wants to do social listening and engagement triage.
More from MaxKmet/idea-validation-agents
All 15 skills in this repoCac Modeler
MaxKmet/idea-validation-agents
Models LTV, CAC by channel, LTV:CAC ratios, and payback period for an indie developer.
Competitor Mapper
MaxKmet/idea-validation-agents
Maps the full competitive landscape — direct, indirect, substitute, and emerging competitors — with positioning gap analysis, review mining, and marketinsights-calibrated saturation scoring.
Decision Memo
MaxKmet/idea-validation-agents
Writes a concise, human-readable decision brief summarizing the full validation analysis — including score, verdict, RAT experiment, pre-mortem, and tier-appropriate next actions.
Desire Evaluator
MaxKmet/idea-validation-agents
Scores the strength of core human desire motivations (survival, status, belonging, control, curiosity) for a given app idea to predict user pull and retention potential.
Distribution Analysis
MaxKmet/idea-validation-agents
Evaluates organic reach potential, paid feasibility, platform distribution advantages, creator economy fit, and founder edge for a B2C app idea.
Idea Scoring
MaxKmet/idea-validation-agents
Aggregates all dimension scores into a final idea score (0–100) and issues a verdict.
Related
Works with
Questions about Trend To Product Mapper
What does Trend To Product Mapper do?
Maps viral social content and trending topics to concrete app opportunities by extracting the underlying problem and validating monetization fit. Trend To Product Mapper is an agent skill from MaxKmet/idea-validation-agents. Maps viral social content and trending topics to concrete app opportunities by extracting the underlying problem and validating monetization fit.
When should I use Trend To Product Mapper?
Trend To Product Mapper fits situations like: tasks that involve Social media posts; tasks that involve Health and fitness tracking; tasks that involve Brainstorming.
How do I install Trend To Product Mapper in Claude Code?
Run `npx skills add MaxKmet/idea-validation-agents --skill trend-to-product-mapper -a claude-code`. Or copy the skill folder (skills/trend-to-product-mapper in MaxKmet/idea-validation-agents) into .claude/skills/trend-to-product-mapper in your project. Claude Code loads it when a task matches its description.
How do I install Trend To Product Mapper in Codex?
Run `npx skills add MaxKmet/idea-validation-agents --skill trend-to-product-mapper -a codex`. Or copy the skill folder (skills/trend-to-product-mapper in MaxKmet/idea-validation-agents) into .agents/skills/trend-to-product-mapper in your project. Codex loads it when a task matches its description.
Can I use Trend To Product Mapper in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add MaxKmet/idea-validation-agents --skill trend-to-product-mapper -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/trend-to-product-mapper, .gemini/skills/trend-to-product-mapper, .github/skills/trend-to-product-mapper and .opencode/skills/trend-to-product-mapper in your project.
What does Trend To Product Mapper need to run?
SKILL.md names no scripts, command-line tools or credentials: Trend To Product Mapper is instructions for the agent only.
Does Trend To Product Mapper access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Trend To Product Mapper safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Trend To Product Mapper use?
Trend To Product Mapper is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Trend To Product Mapper use?
About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Trend To Product Mapper?
Skills that share tags, products or a category with Trend To Product Mapper: Viral Short Form Ideas (vyralcontent/content-skills, 134 stars), Content Coach (Blotato-Inc/blotato-skills, 183 stars), Brainstorm Linkedin (techwolf-ai/ai-first-toolkit, 132 stars) and Trendwatch (nestyme/awesome-prompts, 151 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Trend To Product Mapper?
MaxKmet (a GitHub user) maintains it in MaxKmet/idea-validation-agents, which has 478 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on June 16, 2026.
Source: MaxKmet/idea-validation-agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.