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 skills/nirholas/xactions/lead-generationnpx skills add nirholas/XActions --skill lead-generationgit clone --depth 1 https://github.com/nirholas/XActionsWhat 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 | $0.00053 | $0.00742 |
| Opus 5 | $0.00026 | $0.00371 |
| Sonnet 5 | $0.00011 | $0.00148 |
| Haiku 4.5 | $0.00005 | $0.00074 |
Grade A, and why
lead-generation 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead Generation
MCP-powered workflow for finding and qualifying B2B leads from X/Twitter conversations and profiles.
MCP Tools Used
| Tool | Purpose |
|---|---|
x_search_tweets |
Find conversations by keyword/intent |
x_get_profile |
Qualify leads with profile data |
x_get_tweets |
Assess activity level and interests |
x_get_followers |
Check audience size and quality |
x_get_following |
Identify competitor usage / peer network |
Workflow
- Define search queries -- Build 3-5 keyword queries combining pain points, competitor names, or buying signals (e.g., "looking for {tool}", "anyone recommend {category}", "switching from {competitor}").
- Search conversations -- Call
x_search_tweetsfor each query withlimit: 30. Collect unique usernames. - Qualify profiles -- Call
x_get_profilefor each. Filter by: has bio, followers > 100, account age > 6 months. - Score intent -- Assign 1-5 score:
- 5: Explicit buying intent ("need a tool for...", "budget approved")
- 4: Comparing solutions ("X vs Y", "switching from")
- 3: Pain point discussion ("struggling with...")
- 2: Topic interest (engages with industry content)
- 1: Tangential mention
- Gather context -- For top leads (4-5), call
x_get_tweetswithlimit: 20. - Check network -- Call
x_get_followingfor high-value leads to see competitor follows. - Export lead list -- Format as structured output.
Browser Script Integration
Enhance MCP workflows with browser scripts:
| Goal | Script |
|---|---|
| Monitor keywords in real-time | src/keywordMonitor.js |
| Analyze potential lead's audience | src/audienceDemographics.js |
| Check overlap with your audience | src/audienceOverlap.js |
| Engage with leads' content | src/engagementBooster.js |
| Auto-follow qualified leads | src/automation/keywordFollow.js |
Output Template
## Lead List: {search_topic}
Generated: {date} | Total qualified: {count}
| Username | Score | Followers | Signal | Tweet URL |
|----------|-------|-----------|--------|-----------|
| @{user} | {1-5} | {count} | {type} | {url} |
### High-Priority Leads (Score 4-5)
**@{username}** -- Score: {n}/5
- Signal: "{tweet excerpt}"
- Bio: {bio}
- Suggested approach: {personalized outreach note}
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 · 74 lines · 53 tokens per session scan A 329c4633bcf7
lead-generation is a skill published in the GitHub repository nirholas/XActions (496 stars, last pushed 5d ago), licensed Apache-2.0. It adds 53 tokens to every session and 742 once invoked, about $0.0003 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 2026-08-30.
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