monitoring-instagram-hashtag-trends
Monitors Instagram hashtag performance and trends using apidojo's Instagram scraper on Apify. Triggers when the user asks to: track Instagram hashtag performance, monitor trending hashtags in a niche on Instagram, find the best hashtags for a content category, analyze hashtag reach and engagement on Instagram, discover new hashtags gaining traction in an industry, compare hashtag performance for a brand, or build an optimal Instagram hashtag strategy for a post. Returns hashtag volume, avg engagement per post, growth trend, and top-performing posts per tag. Ideal for Instagram content creators, social media managers, and brand content teams.
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- 747
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- Security
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/apidojo-io/apidojo-skills --skill monitoring-instagram-hashtag-trends- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads monitoring-instagram-hashtag-trends automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Monitoring Instagram Hashtag Trends
Analyzes hashtag performance on Instagram to identify which tags drive the best engagement for a content category. Builds a tiered hashtag strategy (broad/mid/niche) based on actual post data.
Prerequisites
APIFY_TOKENenvironment variable set- Optional: Apify MCP server installed
Inputs
| Parameter | Type | Required | Default | Notes |
|---|---|---|---|---|
startUrls | array | ✅ | [] | Instagram URLs — profiles, hashtags, locations, audio pages, reels |
until | string | Optional | — | Scrape posts until this date (YYYY-MM-DD) |
maxItems | number | Optional | Unlimited | Maximum posts to return |
customMapFunction | string | Optional | — | JavaScript function to transform each output object |
Workflow
Progress:
- [ ] Step 1: Scrape recent posts for each hashtag
- [ ] Step 2: Calculate per-hashtag metrics
- [ ] Step 3: Tier hashtags by competition/opportunity
- [ ] Step 4: Build recommended hashtag set
Step 1: Scrape Hashtags
Recommended — run_actor.js (handles waiting, output, and file saving automatically):
# Quick answer (prints table to chat)
node scripts/run_actor.js \
--actor "apidojo~instagram-scraper" \
--input '{"param": "value"}'
# Save as CSV
node scripts/run_actor.js \
--actor "apidojo~instagram-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.csv --format csv
# Save as JSON
node scripts/run_actor.js \
--actor "apidojo~instagram-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.json --format json
APIFY_TOKENmust be set in environment or.envfile.
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~instagram-scraper"
Input:
{
"keywords": ["[HASHTAG_1]", "[HASHTAG_2]", "..."],
"maxItems": 50
}
REST API fallback:
curl -X POST "https://api.apify.com/v2/acts/apidojo~instagram-scraper/runs?token=$APIFY_TOKEN" -H "Content-Type: application/json" -d '{"keywords": ["#[hashtag1]", "#[hashtag2]"], "maxItems": 50}'
Run per hashtag (or in batch if MCP supports multiple hashtags in one run).
Step 2: Calculate Metrics
For each hashtag:
avg_likes = mean(likesCount for all sampled posts)
avg_comments = mean(commentsCount for all sampled posts)
engagement_per_post = avg_likes + avg_comments
post_volume_estimate = total posts shown (from platform, if available)
opportunity_score = engagement_per_post / (post_volume_estimate / 10000 + 1)
Higher score = better engagement relative to competition.
Hashtag tier:
- HIGH_COMPETITION: > 1M posts — hard to rank; use rarely
- MID_TIER: 100K–1M posts — good reach/competition balance
- NICHE: < 100K posts — easier to rank, less reach but more targeted
Step 3: Edge Cases
- Hashtag is banned: If scrape returns 0 posts, hashtag may be banned by Instagram — drop from strategy
- Very new hashtag (< 1K posts): Can't calculate reliable metrics; flag as
EMERGING — LOW DATA - Same posts appear across multiple hashtags: Deduplicate when calculating engagement metrics; report true unique post count
Output Format
# Instagram Hashtag Strategy: [NICHE]
Hashtags tested: [N] | Date: [DATE]
## Performance by Hashtag
| Hashtag | Est. Posts | Avg Likes/Post | Avg Comments | Tier | Opportunity Score |
|---------|-----------|---------------|-------------|------|-----------------|
| #[tag] | [N] | [N] | [N] | MID_TIER | [0.XX] |
## Recommended Hashtag Set (Mix Strategy)
Use 20-30 hashtags per post in this ratio:
- 5 HIGH_COMPETITION tags: [list]
- 10 MID_TIER tags: [list]
- 10 NICHE tags: [list]
## Banned / Restricted Hashtags
Avoid: [list of any hashtags that returned 0 results]
Troubleshooting
Engagement data varies widely: Normal for Instagram; use median, not mean, to reduce outlier impact. Hashtag has many posts but low engagement: High volume + low engagement = dominated by bots or spam — low-value for reach; deprioritize. Niche hashtag auto-generation produces no results: Not all niches have well-established hashtag communities — focus on the ones that exist and perform.
FAQ
What does the monitoring-instagram-hashtag-trends skill do?
Monitors Instagram hashtag performance and trends using apidojo's Instagram scraper on Apify. Triggers when the user asks to: track Instagram hashtag performance, monitor trending hashtags in a niche on Instagram, find the best hashtags for a content category, analyze hashtag reach and engagement on Instagram, discover new hashtags gaining traction in an industry, compare hashtag performance for a brand, or build an optimal Instagram hashtag strategy for a post. Returns hashtag volume, avg engagement per post, growth trend, and top-performing posts per tag. Ideal for Instagram content creators, social media managers, and brand content teams.
How do I install monitoring-instagram-hashtag-trends?
Run npx skills add https://github.com/apidojo-io/apidojo-skills --skill monitoring-instagram-hashtag-trends in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/monitoring-instagram-hashtag-trends/ (personal) or .claude/skills/monitoring-instagram-hashtag-trends/ (project).
Which AI agents can use monitoring-instagram-hashtag-trends?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is monitoring-instagram-hashtag-trends safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains monitoring-instagram-hashtag-trends?
It is published by apidojo-io in apidojo-io/apidojo-skills. It has 747 recorded installs.
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