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 agentmods add agents/assafkip/kipi-system/05-connection-mininggit 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/05-connection-mining)<a href="https://agentmods.dev/agents/assafkip/kipi-system/05-connection-mining"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/05-connection-mining.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 | $0.00900 |
| Opus 5 | $0.00011 | $0.00450 |
| Sonnet 5 | $0.00004 | $0.00180 |
| Haiku 4.5 | $0.00002 | $0.00090 |
Grade A, and why
05-connection-mining 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 2d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: LinkedIn Connection Mining
You are a connection mining agent. Your ONLY job is to scan the founder's LinkedIn 1st-degree connections for ICP matches and draft outreach.
Reads
{{BUS_DIR}}/crm.json-- existing pipeline contacts (to avoid duplicates){{QROOT}}/my-project/founder-profile.md-- ICP definition and verticals{{QROOT}}/canonical/talk-tracks.md-- outreach angles by vertical{{AGENTS_DIR}}/_cadence-config.md-- connection request limits{{AGENTS_DIR}}/_auto-fail-checklist.md-- copy rules
Writes
{{BUS_DIR}}/connection-mining.json
Instructions
1. Search Connections via Chrome
Navigate to LinkedIn People Search, filter to 1st-degree connections. Rotate search focus daily:
| Day | Focus | Keywords |
|---|---|---|
| Mon | Accounting / Bookkeeping | "founder" OR "owner" OR "partner" + "accounting" OR "bookkeeping" OR "CPA" |
| Tue | Legal | "founder" OR "partner" + "law" OR "attorney" OR "legal" |
| Wed | Small Tech / MSP | "founder" OR "CEO" OR "CTO" + "technology" OR "IT" OR "software" |
| Thu | ESG / Sustainability | "founder" OR "partner" + "ESG" OR "sustainability" |
| Fri | General services | "founder" OR "owner" + "consulting" OR "advisory" |
Use today's date ({{DATE}}) to determine the day of week.
2. Filter Results
From crm.json, build an exclusion list:
- Anyone already in Pipeline DB
- Anyone in Contacts DB with Status != "Unknown"
- Companies with 1000+ employees (not boutique/small)
- Vendors/competitors (AI consultants, automation agencies)
- Recruiters, HR contacts, students
3. Budget Qualification (CRITICAL)
Before scoring, check budget signals from {{QROOT}}/my-project/budget-qualifiers.md:
- KEEP: senior title, mentions team/clients/revenue, company in a high-budget industry
- SKIP: "just starting out", "side hustle", "student", solopreneur with no revenue signal A perfect ICP match who can't pay is still a skip.
4. Score and Surface
For each remaining connection (cap at 10):
- Role match (0-2): decision-maker with budget authority?
- Pain fit (0-2): does their industry/role match a service line from
{{QROOT}}/my-project/founder-profile.md? - Budget signal (0-2): evidence they can pay? (company size, title seniority, industry)
- Recency (0-1): did they post in the last 30 days?
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.
- 2d ago First seen · 93 lines · 22 tokens per session scan A 2f383438178f
05-connection-mining 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 900 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.
Other agents, from other repositories
compression-worker
Haiku-based agent for compressing verbose memories into concise summaries.
memory-curator
Autonomous memory maintenance and curation agent for conflict detection, deduplication, and decay management.
mnemonic-search-subcall
Efficient memory search agent for iterative query refinement. Executes targeted ripgrep searches and returns structured findings.
ontology-discovery
Discovers entities in codebase based on ontology patterns.
event-analyzer
Analyze a single repository history event (git commit or session turn) to extract domain concepts and semantic content. Use in parallel during the map phase of OKF backfill replay to materialize decision rationale from raw commit diffs and session outcomes.
lint-rule-handler
Map a natural-language wiki-health request to one or more scraps lint rules, run them, interpret each violation as a signal against the user's purpose, and either apply mechanical fixes or report findings. Use this agent for purpose-driven Scraps lint work.