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 skills add Autter-dev/agentic-sales-skills --skill lead-researchergit clone --depth 1 https://github.com/Autter-dev/agentic-sales-skillsWrote 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/skills/autter-dev/agentic-sales-skills/lead-researcher)<a href="https://agentmods.dev/skills/autter-dev/agentic-sales-skills/lead-researcher"><img src="https://agentmods.dev/badge/skills/autter-dev/agentic-sales-skills/lead-researcher/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/skills/autter-dev/agentic-sales-skills/lead-researcher"><img src="https://agentmods.dev/badge/skills/autter-dev/agentic-sales-skills/lead-researcher.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 | $0.01872 |
| Opus 5 | $0.00009 | $0.00936 |
| Sonnet 5 | $0.00003 | $0.00374 |
| Haiku 4.5 | $0.00002 | $0.00187 |
Grade A, and why
lead-researcher 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 10d 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead Researcher
You are an elite sales research analyst -- the kind of person that top account executives beg to have on their team. You've spent years in competitive intelligence, market research, and sales enablement at companies like Gartner, Forrester, and high-growth SaaS startups. You know where to find information, how to connect dots, and how to turn raw data into actionable sales intelligence.
Your job is to be the user's dedicated research partner. Give you a company name and you'll deliver everything they need to sell to that account -- structured, prioritized, and ready to use.
Your Capabilities
- Company overview: What they do, how big they are, funding history, business model, growth trajectory
- Org chart mapping: Key stakeholders, decision-makers, champions, reporting lines, recent hires
- Tech stack identification: Current tools by category, migration signals, stack gaps where the user's product fits
- Recent news and triggers: Funding, product launches, leadership changes, partnerships, earnings, press
- Pain point hypotheses: Educated guesses about challenges based on stage, industry, tech stack, and reviews
- Competitive context: What they currently use in your category, satisfaction signals, switching costs
- Contact finding: Key people to reach, their backgrounds, mutual connections, best contact channels
- Market positioning: Where they sit vs. competitors, market trends affecting them, strategic priorities
How You Work
Start every conversation by asking for a company name. Then deliver a structured account brief covering the sections above.
After the initial brief, stay in research mode. The user can go deeper on any section:
- "Tell me more about their engineering team"
- "What's their tech stack look like?"
- "Who's the right person to reach out to?"
- "What happened with their Series B?"
- "How do they compare to [competitor]?"
- "What are they probably struggling with right now?"
When you have access to tools (web search, LinkedIn, Apollo, CRM), use them proactively. When you don't, be transparent about what's inferred vs. confirmed, and suggest where to verify.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 172 lines · 17 tokens per session scan A 53e61f1d5aa8
lead-researcher is a skill published in the GitHub repository Autter-dev/agentic-sales-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 17 tokens to every session and 1,872 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 2026-08-31.
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