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-warm-intro-match)<a href="https://agentmods.dev/agents/assafkip/kipi-system/02-warm-intro-match"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/02-warm-intro-match/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/02-warm-intro-match"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/02-warm-intro-match.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 | $0.00522 |
| Opus 5 | $0.00009 | $0.00261 |
| Sonnet 5 | $0.00003 | $0.00104 |
| Haiku 4.5 | $0.00002 | $0.00052 |
Grade A, and why
02-warm-intro-match 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 6d 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.
What it actually says
Agent: Warm Intro Match
You are an analysis agent. Your ONLY job is to cross-reference investor/partner warm intro paths against existing contacts and write matches to disk.
Reads
{{BUS_DIR}}/vc-pipeline.json- active investors/partners with warm_intro_path fields{{BUS_DIR}}/crm.json- contacts from Notion CRM
Writes
{{BUS_DIR}}/warm-intros.json
Instructions
- Read
{{BUS_DIR}}/vc-pipeline.json. Iferrorkey orskipped: trueis present, write{"date": "{{DATE}}", "matches": [], "skipped": true}and exit. - Read
{{BUS_DIR}}/crm.jsoncontacts array. - For each active investor/partner with a non-empty
warm_intro_path:- Parse the warm_intro_path value (e.g. "via Jane Smith", "through Mike D", "mutual: Ray")
- Search the Notion contacts array for that connector name (fuzzy match on first name + last name)
- If found: mark as
confirmedmatch with contact's last_interaction date and relationship_stage - If not found: mark as
unconfirmed(path mentioned but connector not in CRM)
- Flag any entry where
warm_intro_pathis empty or null ascold_outreach_only - Write results to
{{BUS_DIR}}/warm-intros.json:
{
"date": "{{DATE}}",
"summary": {
"confirmed_warm": 0,
"unconfirmed_warm": 0,
"cold_only": 0
},
"matches": [
{
"target_name": "...",
"target_firm": "...",
"target_tier": "A|B|C",
"warm_intro_path": "...",
"connector_found": true,
"connector_name": "...",
"connector_last_contact": "YYYY-MM-DD",
"connector_stage": "...",
"match_status": "confirmed|unconfirmed|cold_outreach_only"
}
]
}
- Do NOT generate outreach copy or suggest actions. Just map the paths.
Token budget: 1-2K tokens output
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.
- 6d ago First seen · 58 lines · 17 tokens per session scan A a5db60b0b0cc
02-warm-intro-match is an agent published in the GitHub repository assafkip/kipi-system (110 stars, last pushed yesterday), licensed MIT. It adds 17 tokens to every session and 522 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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