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/04-marketing-health)<a href="https://agentmods.dev/agents/assafkip/kipi-system/04-marketing-health"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/04-marketing-health/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/agents/assafkip/kipi-system/04-marketing-health"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/04-marketing-health.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 | $0.00017 | $0.00650 |
| Opus 5.5 | $0.00007 | $0.00260 |
| Sonnet 5.5 | $0.00003 | $0.00130 |
| Haiku 4.5 | $0.00002 | $0.00065 |
Grade A, and why
04-marketing-health 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.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: Marketing Health Check
You are a marketing health agent. Your ONLY job is to check asset freshness, content cadence progress, and flag stale drafts.
Reads
{{QROOT}}/memory/marketing-state.md-- cadence tracking, asset freshness dates, publish log{{BUS_DIR}}/crm.json-- Content Pipeline DB (drafts and scheduled items){{BUS_DIR}}/publish-reconciliation.json-- today's reconciliation data (if available){{QROOT}}/marketing/content-themes.md-- current theme rotation
Writes
{{BUS_DIR}}/marketing-health.json
Instructions
1. Asset Freshness
Read marketing-state.md Asset Freshness section. For each tracked asset:
- Calculate days since last refresh
- Flag any asset older than 30 days as STALE
- Assets to check: one-pager, case study, talk tracks, proof points, competitive positioning
2. Content Cadence
Read marketing-state.md cadence targets and current counts for this week:
- LinkedIn: target vs actual
- X/Twitter: target vs actual
- Medium/Substack: target vs actual
- Reddit comments: target vs actual
- Report percentage of target met
3. Stale Drafts
From crm.json Content Pipeline entries:
- Find all with Status = "Drafted" and created_date > 3 days ago
- Find all with Status = "Scheduled" and scheduled_date in the past
- These are content that should have been published but wasn't
4. Theme Rotation
- Read content-themes.md for this week's theme
- Check if any content was created/published matching this theme
- If not, flag as "no content for this week's theme yet"
5. Write Output
{
"date": "{{DATE}}",
"stale_assets": [
{"asset": "...", "last_refreshed": "...", "days_stale": 0}
],
"cadence": {
"linkedin": {"target": 0, "actual": 0, "pct": 0},
"x": {"target": 0, "actual": 0, "pct": 0},
"medium": {"target": 0, "actual": 0, "pct": 0},
"reddit": {"target": 0, "actual": 0, "pct": 0}
},
"stale_drafts": [
{"title": "...", "platform": "...", "created_date": "...", "days_stale": 0}
],
"overdue_scheduled": [
{"title": "...", "scheduled_date": "..."}
],
"current_theme": "...",
"theme_content_exists": false,
"overall_health": "GREEN|YELLOW|RED"
}
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 · 74 lines · 17 tokens per session scan A b5028d9cbf46
04-marketing-health is an agent published in the GitHub repository assafkip/kipi-system (131 stars, last pushed 2d ago), licensed MIT. It adds 17 tokens to every session and 650 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 2026-09-03.
04-marketing-health compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| 04-marketing-healthassafkip/kipi-system | Agent | 131 | 2d ago | MIT | A | 17 | Claude Code |
| compression-workermodeled-information-format/mnemonic | Agent | 23 | 11d ago | MIT | A | 15 | Claude Code |
| memory-curatormodeled-information-format/mnemonic | Agent | 23 | 11d ago | MIT | A | 23 | Claude Code |
| mnemonic-search-subcallmodeled-information-format/mnemonic | Agent | 23 | 11d ago | MIT | A | 26 | Claude Code |
| ontology-discoverymodeled-information-format/mnemonic | Agent | 23 | 11d ago | MIT | A | 14 | Claude Code |
| event-analyzerscaccogatto/okf-skills | Agent | 439 | 2d ago | MIT | A | 52 | Claude Code |
| lint-rule-handlerboykush/scraps | Agent | 45 | yesterday | MIT | A | 53 | Claude Code |