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 guia-matthieu/clawfu-skills --skill social-analyticsgit clone --depth 1 https://github.com/guia-matthieu/clawfu-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/guia-matthieu/clawfu-skills/social-analytics)<a href="https://agentmods.dev/skills/guia-matthieu/clawfu-skills/social-analytics"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/social-analytics/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/guia-matthieu/clawfu-skills/social-analytics"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/social-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00035 | $0.01420 |
| Opus 5 | $0.00017 | $0.00710 |
| Sonnet 5 | $0.00007 | $0.00284 |
| Haiku 4.5 | $0.00003 | $0.00142 |
Grade A, and why
social-analytics 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 9d 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 — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Analytics
Analyze social media profiles and calculate engagement metrics - understand what content works for competitors and your own accounts.
When to Use This Skill
- Competitor analysis - Audit competitor social presence
- Engagement benchmarking - Calculate and compare engagement rates
- Content analysis - Identify top-performing post types
- Profile audit - Assess social media health
- Reporting - Generate social performance reports
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Structures analysis frameworks | Metric definitions |
| Identifies patterns in data | Business interpretation |
| Creates visualization templates | Dashboard design |
| Suggests optimization areas | Action priorities |
| Calculates statistical measures | Decision thresholds |
Dependencies
pip install click pandas requests beautifulsoup4
# For authenticated API access:
pip install tweepy instaloader
Commands
Analyze Profile
python scripts/main.py analyze @competitor --platform twitter
python scripts/main.py analyze @brand --platform instagram
Calculate Engagement
python scripts/main.py engagement @profile --platform twitter --days 30
python scripts/main.py engagement @profile --platform linkedin --posts 50
Find Top Posts
python scripts/main.py top-posts @profile --platform twitter --count 10
python scripts/main.py top-posts @profile --metric likes
Export Data
python scripts/main.py export @profile --platform twitter --format csv
python scripts/main.py export @profile --platform instagram --output report.json
Compare Profiles
python scripts/main.py compare @brand1 @brand2 @brand3 --platform twitter
Examples
Example 1: Competitor Social Audit
# Analyze competitor profile
python scripts/main.py analyze @competitor_brand --platform twitter
# Output:
# Profile Analysis: @competitor_brand
# ─────────────────────────────────────
# Followers: 45,230
# Following: 1,234
# Total Posts: 2,456
# Avg Likes: 234
# Avg Retweets: 45
# Engagement: 2.3%
# Post Frequency: 3.2/day
# Top Hashtags: #marketing, #growth, #startup
What ships with it
2 files 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.
- 9d ago First seen · 196 lines · 35 tokens per session scan A f7b3e564d382
social-analytics is a skill published in the GitHub repository guia-matthieu/clawfu-skills (149 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 1,420 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 2026-09-03.
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