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 tough-tongue/demo-prep-skills --skill research-prospectgit clone --depth 1 https://github.com/tough-tongue/demo-prep-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/tough-tongue/demo-prep-skills/research-prospect)<a href="https://agentmods.dev/skills/tough-tongue/demo-prep-skills/research-prospect"><img src="https://agentmods.dev/badge/skills/tough-tongue/demo-prep-skills/research-prospect/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/tough-tongue/demo-prep-skills/research-prospect"><img src="https://agentmods.dev/badge/skills/tough-tongue/demo-prep-skills/research-prospect.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 | $0.00049 | $0.01448 |
| Opus 5 | $0.00024 | $0.00724 |
| Sonnet 5 | $0.00010 | $0.00290 |
| Haiku 4.5 | $0.00005 | $0.00145 |
Grade A, and why
research-prospect 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prospect Research
Research a prospect company and contact to produce a structured intelligence brief. This skill gathers information from the company's website and the contact's LinkedIn profile, then cross-references with your company-profile.md to find personalization hooks.
When to Use
- Before writing any outreach (cold email, LinkedIn message)
- Before a demo or meeting (this skill is called automatically by
demo-prep) - When the user says "research [name] at [company]"
- When you need to understand a prospect before generating any output
Required Inputs
Ask the user for:
Company: [Name or website URL]
Contact: [Name and title — optional for company-only research]
If they only provide a name and company, that's enough. Research the rest.
Process
1. Load Company Profile
Read company-profile.md from the workspace root. You need this to:
- Identify shared connections between the user and the prospect
- Match the prospect's pain points to the user's product
- Determine if this company fits the user's ICP
If company-profile.md doesn't exist, tell the user: "Run the setup-company skill first to set up your profile. This makes research much more useful."
2. Research the Company
Navigate to the company's website and gather:
| What to Find | Where to Look |
|---|---|
| What they do | Homepage hero section, About page |
| Who they sell to | Pricing page, case studies, customer logos |
| Company size | About page, LinkedIn company page, job postings |
| Sales model | Pricing page structure, "Book a Demo" vs "Start Free Trial" |
| Recent news | Blog, press page, recent funding announcements |
| Tech stack signals | Job postings, integrations page |
| Demo / trial motion | CTA buttons, pricing page, "how it works" |
Also check for (see research checklist):
- Whether they have a "Book a Demo" button (relevant for demo automation)
- Whether they're hiring for roles related to the user's product
- Recent product launches or pivots
- Customer testimonials that reveal their value prop
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 · 155 lines · 49 tokens per session scan A 418cc838713b
research-prospect is a skill published in the GitHub repository tough-tongue/demo-prep-skills (5 stars, last pushed 6mo ago), licensed MIT. It adds 49 tokens to every session and 1,448 once invoked, about $0.0002 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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