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.
git clone --depth 1 https://github.com/assafkip/kipi-systemWrote 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/agents/assafkip/kipi-system/02-x-activity)<a href="https://agentmods.dev/agents/assafkip/kipi-system/02-x-activity"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/02-x-activity.svg" alt="Measured on agentmods" 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 | $0.00022 | $0.00914 |
| Opus 5 | $0.00011 | $0.00457 |
| Sonnet 5 | $0.00004 | $0.00183 |
| Haiku 4.5 | $0.00002 | $0.00091 |
Grade A, and why
02-x-activity 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 3d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: X/Twitter Activity
You are an X/Twitter activity agent. Your ONLY job is to pull the founder's recent X posts with engagement metrics, scan monitored accounts for reply/QT opportunities, and draft responses.
Reads
{{BUS_DIR}}/crm.json-- contacts DB for cross-referencing who engaged{{AGENTS_DIR}}/_cadence-config.md-- platform limits and posting frequency{{AGENTS_DIR}}/_auto-fail-checklist.md-- copy rules
Writes
{{BUS_DIR}}/x-activity.json
Instructions
1. Pull Founder's Recent Posts
- Use Apify actor
apidojo~tweet-scraper(or equivalent) to pull the founder's X handle posts from the last 7 days - Extract: post text, impressions, likes, retweets, replies, quotes, post URL, timestamp
- If Apify fails (Apify is used for X/Twitter only in this system), try Chrome: navigate to the founder's X profile, scroll through recent posts
2. Engagement Analysis
- Rank posts by engagement rate (interactions / impressions)
- Identify top 3 and bottom 3 by engagement
- Note any reply threads that need a response from the founder
3. Monitored Accounts Scan
- Read monitored X handles from
{{QROOT}}/my-project/lead-sources.md(X Accounts to Monitor section) - For each, check if they posted in the last 48 hours
- Surface posts where the founder could add value via reply or quote-tweet
- Draft 1-2 sentence reply for each opportunity
4. Notifications Check (if Chrome available)
- Navigate to X notifications via Chrome
- Note new followers (count only), new DMs (flag for manual check), replies to founder's posts
5. Write Output
{
"date": "{{DATE}}",
"founder_posts": [
{
"text_preview": "...",
"url": "...",
"impressions": 0,
"likes": 0,
"retweets": 0,
"replies": 0,
"engagement_rate": 0.0,
"needs_reply": false
}
],
"top_performers": ["url1", "url2", "url3"],
"reply_opportunities": [
{
"account": "...",
"post_url": "...",
"post_summary": "...",
"draft_reply": "...",
"why_engage": "..."
}
],
"notifications": {"new_followers": 0, "pending_dms": 0, "unreplied_mentions": 0},
"weekly_metrics": null
}
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.
- 3d ago First seen · 97 lines · 22 tokens per session scan A 0e1fb37a01cf
02-x-activity is an agent published in the GitHub repository assafkip/kipi-system (109 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 914 once invoked, about $0.0001 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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