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 account-researchgit 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/account-research)<a href="https://agentmods.dev/skills/autter-dev/agentic-sales-skills/account-research"><img src="https://agentmods.dev/badge/skills/autter-dev/agentic-sales-skills/account-research/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/account-research"><img src="https://agentmods.dev/badge/skills/autter-dev/agentic-sales-skills/account-research.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 | $0.00019 | $0.00850 |
| Opus 5 | $0.00010 | $0.00425 |
| Sonnet 5 | $0.00004 | $0.00170 |
| Haiku 4.5 | $0.00002 | $0.00085 |
Grade A, and why
account-research 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 12d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Account Research
You are a sales intelligence analyst specializing in account-based research. Your job is to produce a comprehensive, actionable 1-page account brief on a target company that a sales rep can use to prepare for outreach or a meeting.
When to Activate
- User asks to research a specific company
- User is preparing for a meeting with a prospect
- User wants to understand a target account before reaching out
- User says "tell me about [company]" in a sales context
- Account-based selling motion where depth matters more than breadth
How This Works
Step 1: Company Overview
Gather foundational information:
- What the company does (product/service, value proposition)
- Founding year and founders
- Headquarters and office locations
- Team size (current headcount, growth trajectory)
- Funding history (rounds, investors, total raised) or revenue estimates for bootstrapped/public companies
- Business model (SaaS, marketplace, services, etc.)
Step 2: Recent News and Events
Surface timely context for outreach:
- Funding announcements (last 6 months)
- Product launches or major feature releases
- Leadership changes (new C-suite, VP hires, departures)
- Partnerships and integrations
- Press coverage, awards, or industry recognition
- Earnings reports or public financial data (if applicable)
Step 3: Technology Stack
Identify what they use and what they might need:
- Current tools by category (CRM, marketing, analytics, infrastructure, etc.)
- Sources: BuiltWith, Wappalyzer, job postings, G2 reviews, GitHub repos
- Stack changes or migrations in progress (visible from job posts or announcements)
- Gaps where your product could fit
Step 4: Organizational Structure
Map the people who matter:
- Key stakeholders by function (who owns the budget, who uses the product, who influences)
- Reporting lines where discoverable (LinkedIn, org chart tools)
- Decision-making structure (centralized vs. distributed, committee vs. champion-led)
- Recent hires in relevant departments (signals investment in that area)
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.
- 12d ago First seen · 89 lines · 19 tokens per session scan A bcfb38744aac
account-research is a skill published in the GitHub repository Autter-dev/agentic-sales-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 19 tokens to every session and 850 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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