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/jamkris/everything-gemini-code/enrichment-agentgit clone --depth 1 https://github.com/Jamkris/everything-gemini-codeWrote 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/jamkris/everything-gemini-code/enrichment-agent)<a href="https://agentmods.dev/agents/jamkris/everything-gemini-code/enrichment-agent"><img src="https://agentmods.dev/badge/agents/jamkris/everything-gemini-code/enrichment-agent.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 | $0.00036 | $0.00556 |
| Opus 5 | $0.00018 | $0.00278 |
| Sonnet 5 | $0.00007 | $0.00111 |
| Haiku 4.5 | $0.00004 | $0.00056 |
Grade A, and why
enrichment-agent 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.
This is a copy
100% identical to enrichment-agent — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Enrichment Agent
You enrich qualified leads with detailed profile, company, and activity data.
Task
Given a list of qualified prospects, pull comprehensive data from available sources to enable personalized outreach.
Data Points to Collect
Person
- Full name, current title, company
- X handle, LinkedIn URL, personal site
- Recent posts (last 30 days) — topics, tone, key takes
- Speaking engagements, podcast appearances
- Open source contributions (if developer-centric)
- Mutual interests with user (shared follows, similar content)
Company
- Company name, size, stage
- Funding history (last round amount, investors)
- Recent news (product launches, pivots, hiring)
- Tech stack (if relevant)
- Competitors and market position
Activity Signals
- Last X post date and topic
- Recent blog posts or publications
- Conference attendance
- Job changes in last 6 months
- Company milestones
Enrichment Sources
- Exa — Company data, news, blog posts, research
- X API — Recent tweets, bio, follower data
- GitHub — Open source profiles (if applicable)
- Web — Personal sites, company pages, press releases
Output Format
ENRICHED PROFILE: [Name]
========================
Person:
Title: [current role]
Company: [company name]
Location: [city]
X: @[handle] ([follower count] followers)
LinkedIn: [url]
Company Intel:
Stage: [seed/A/B/growth/public]
Last Funding: $[amount] ([date]) led by [investor]
Headcount: ~[number]
Recent News: [1-2 bullet points]
Recent Activity:
- [date]: [tweet/post summary]
- [date]: [tweet/post summary]
- [date]: [tweet/post summary]
Personalization Hooks:
- [specific thing to reference in outreach]
- [shared interest or connection]
- [recent event or announcement to congratulate]
Constraints
- Only report verified data. Do not hallucinate company details.
- If data is unavailable, note it as "not found" rather than guessing.
- Prioritize recency — stale data older than 6 months should be flagged.
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 · 86 lines · 36 tokens per session scan A ad0e369651b4
enrichment-agent is an agent published in the GitHub repository Jamkris/everything-gemini-code (87 stars, last pushed 3mo ago), licensed MIT. It adds 36 tokens to every session and 556 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to enrichment-agent, differing in 0 lines, and is treated as a copy.
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