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.
npx skills add sandbaseai/sandbase-skills --skill instagram-researchgit clone --depth 1 https://github.com/sandbaseai/sandbase-skillsWrote 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.
[](https://agentmods.dev/skills/sandbaseai/sandbase-skills/instagram-research)<a href="https://agentmods.dev/skills/sandbaseai/sandbase-skills/instagram-research"><img src="https://agentmods.dev/badge/skills/sandbaseai/sandbase-skills/instagram-research/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.
<a href="https://agentmods.dev/skills/sandbaseai/sandbase-skills/instagram-research"><img src="https://agentmods.dev/badge/skills/sandbaseai/sandbase-skills/instagram-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00044 | $0.00546 |
| Opus 5 | $0.00022 | $0.00273 |
| Sonnet 5 | $0.00009 | $0.00109 |
| Haiku 4.5 | $0.00004 | $0.00055 |
Grade A, and why
instagram-research 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instagram Research
Instagram content and creator research through SandBase. Search posts, analyze profiles, track hashtag trends, and gather competitive intelligence. Read the API map before selecting a capability.
Call SandBase capabilities
For every selected tool, call sandbase_describe_tool first and use only arguments in its current input schema. Then call sandbase_call_tool with the exact tool_name.
Operating principles
- Use Instagram data for market research and competitive intelligence only.
- Preserve attribution: include post URLs, usernames, engagement metrics, dates.
- Respect user privacy — focus on public accounts and public content.
- Never attempt to follow, like, comment, or message on behalf of the user.
Workflow
1. Search and discover
Use instagram_v3_general_search to find accounts, hashtags, and places.
Use instagram_v3_hashtag_posts to track content around specific hashtags.
Use instagram_v3_explore to discover trending content.
2. Analyze profiles
Use instagram_v3_user_profile for account details (bio, followers, post count).
Use instagram_v3_user_posts for recent content and engagement patterns.
Use instagram_v3_user_reels for Reels strategy analysis.
Use instagram_v3_user_highlights for curated content themes.
3. Analyze content
Use instagram_v3_post_info for detailed post metrics (likes, comments, caption).
Use instagram_v3_post_comments for audience sentiment and engagement quality.
Use instagram_v3_post_likes to see who engages with content.
4. Location and music research
Use instagram_v3_location_posts for location-based content discovery.
Use instagram_v3_music_posts to find content using specific audio.
Output
Return: search results, profile analysis (followers, engagement rate, content themes), hashtag performance, content patterns, and competitive positioning.
Example tasks
- "Analyze @competitor's Instagram — posting frequency, engagement rate, content themes."
- "Find top posts for #[hashtag] in the last week."
- "Who are the top Instagram influencers in [niche] with 50K-500K followers?"
- "What content format performs best for [brand] on Instagram?"
- "Track how [campaign hashtag] is performing in terms of post volume and engagement."
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 58 lines · 44 tokens per session scan A 3af4c4b2cf7c
instagram-research is a skill published in the GitHub repository sandbaseai/sandbase-skills (145 stars, last pushed 2d ago), licensed Apache-2.0. It adds 44 tokens to every session and 546 once invoked, about $0.0002 per session on Opus 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.
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