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 Ken-Technology/cold-email-skills --skill client-researchgit clone --depth 1 https://github.com/Ken-Technology/cold-email-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/ken-technology/cold-email-skills/client-research)<a href="https://agentmods.dev/skills/ken-technology/cold-email-skills/client-research"><img src="https://agentmods.dev/badge/skills/ken-technology/cold-email-skills/client-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/ken-technology/cold-email-skills/client-research"><img src="https://agentmods.dev/badge/skills/ken-technology/cold-email-skills/client-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 | $0.00099 | $0.01338 |
| Opus 5 | $0.00049 | $0.00669 |
| Sonnet 5 | $0.00020 | $0.00268 |
| Haiku 4.5 | $0.00010 | $0.00134 |
Grade A, and why
client-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 9d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Client Research Skill
Synthesize multiple research sources into a comprehensive client strategy document optimized for both human review and downstream AI agents (GTM strategy, list building, email copywriting).
Required Context
Before generating the research document, load all available client sources. {workspace} = the client campaign workspace (default ./cold-email/{slug}/ under the current directory):
Directory Structure Reference:
{workspace}/
├── research.md # Existing research (preserve metadata if updating) - THIS skill's output
├── notes.md # Optional client preferences
├── research/ # Source material: scraped website content,
│ └── website/ # transcripts, documents the user dropped in
└── {plan folders}/ # Past campaign plans (note what worked)
Sources may also arrive as user uploads or paths given in the conversation - use whatever is provided.
Inputs
Expect one or more of these source types:
- Meeting recordings/transcripts (Fireflies, Otter, Gong, etc.)
- Scraped website content
- Product documentation
- Competitor analysis
- Customer testimonials or case studies
- Sales materials
Output Format
Generate ONE document, {workspace}/research.md, with a quick-reference summary on top followed by the comprehensive research. This single file is what every downstream campaign skill reads.
Part 1: Summary (top of research.md)
Quick-reference section for daily use. See references/context-template.md for the exact structure. Key sections:
- Header metadata (client slug, created date, owner)
- Elevator Pitch - Short hook answering: "If I met {ICP} in an elevator with {Company}, what should I say in a couple seconds to make them really hooked?"
- About the Company - 3-paragraph executive summary
- Target Audience - Condensed ICP (1-2 paragraphs)
- Core Problems Solved - Bulleted list (3-5 items)
- Key Assets - Top 3 lead magnets (table format)
- Case Studies - Top 3 results (table format)
- Quick Links - Website, other client links
What ships with it
2 files 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.
- 9d ago First seen · 145 lines · 99 tokens per session scan A bcf8c9d21e13
client-research is a skill published in the GitHub repository Ken-Technology/cold-email-skills (3 stars, last pushed 12d ago), licensed MIT. It adds 99 tokens to every session and 1,338 once invoked, about $0.0005 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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