An Instagram analysis skill that collects live account and post data, then calculates engagement measures and compares results with past account benchmarks.

Use it to review recent posts, inspect reach, impressions, saves, shares, views, and profile visits, and detect performance patterns.

It helps identify which posts perform well and avoids filling missing results with estimates or invented numbers.

ig-analyze — Skill for Claude Code by nicojunk/claude-ig

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add nicojunk/claude-ig --skill ig-analyze

Clone the repo

git clone --depth 1 https://github.com/nicojunk/claude-ig

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/nicojunk/claude-ig/ig-analyze/github.svg)](https://agentmods.dev/skills/nicojunk/claude-ig/ig-analyze)

Your own site

<a href="https://agentmods.dev/skills/nicojunk/claude-ig/ig-analyze"><img src="https://agentmods.dev/badge/skills/nicojunk/claude-ig/ig-analyze/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/nicojunk/claude-ig/ig-analyze"><img src="https://agentmods.dev/badge/skills/nicojunk/claude-ig/ig-analyze.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,279 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00037	$0.01279
Opus 5.5	$0.00015	$0.00512
Sonnet 5.5	$0.00007	$0.00256
Haiku 4.5	$0.00004	$0.00128

Measured 2mo ago against content hash 9484b8b053d6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ig-analyze scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/ig-analyze/SKILL.md · 157 lines

How it starts

The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.

IG Analyze -- API-driven Instagram performance analysis

Key references:

references/account-baseline.md -- current benchmarks, follower count, historical averages
references/scoring-system.md -- metric definitions, scoring thresholds, weighted formulas

CRITICAL RULE: This skill MUST use live API data. Never guess, estimate, or fabricate metrics. If an API call fails, report the failure. Do not fill in placeholder numbers.

Phase 1: Data Collection

Pull data using Instagram MCP tools in this order:

Account overview:
```
mcp__claude_ai_Instagram_MCP__get_user_info
```
Capture: follower count, following count, media count, bio, profile pic.
Recent media:
```
mcp__claude_ai_Instagram_MCP__get_user_media
```
Fetch the most recent 25 posts. For each, capture: id, type (carousel/reel/image), timestamp, caption, like count, comment count.
Post-level insights (for each post):
```
mcp__claude_ai_Instagram_MCP__get_post_insights
```
Capture: reach, impressions, saves, shares, video views (if reel), profile visits.
Account-level insights:
```
mcp__claude_ai_Instagram_MCP__get_user_insights
```
Capture: reach, impressions, follower growth, profile visits over the requested period.

Bundle independent API calls in parallel where possible. Do not make serial calls when parallel is available.

Phase 2: Metric Calculation

Calculate the following metrics from the collected data:

Per-Post Metrics

Metric	Formula
Engagement Rate	(likes + comments + saves + shares) / reach * 100
Save Rate	saves / reach * 100
DM-Send Rate	shares / reach * 100
Completion Rate (Reels)	average watch time / duration * 100
Reach-to-Follower Ratio	reach / follower_count * 100

Account-Level Metrics

Metric	Formula
Average Engagement Rate	mean of per-post engagement rates
Save Rate Trend	save rate comparison: last 7 posts vs prior 7
Reach Growth	(current period reach - prior period reach) / prior * 100
Content Mix	% reels vs % carousels vs % single images

Read the full file on GitHub · 157 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 157 lines · 37 tokens per session scan A 9484b8b053d6

Subscribe to this mod's changes

ig-analyze is a skill published in the GitHub repository nicojunk/claude-ig (23 stars, last pushed 2mo ago), licensed MIT. It adds 37 tokens to every session and 1,279 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Analytics and metrics Marketing and SEO

ig-analyze next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
ig-analyzenicojunk/claude-ig	Skill	23	2mo ago	MIT	A	37	Claude Code
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playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code