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 | $0.00074 | $0.01930 |
| Opus 5.5 | $0.00030 | $0.00772 |
| Sonnet 5.5 | $0.00015 | $0.00386 |
| Haiku 4.5 | $0.00007 | $0.00193 |
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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Client Research Skill
Turn a company's sources into the research every campaign skill builds on: research.md in the campaign workspace, with a quick-reference summary, the full research for strategy and copy, and a short company context that personalization prompts run with.
{workspace} = the campaign workspace, default ./cold-email/{slug}/ under the current directory:
{workspace}/
├── research.md # this skill's output (keep its metadata when updating)
├── notes.md # optional: the client's preferences
└── research/ # source material: website pages, transcripts, documents
└── website/
When the company keeps a knowledge folder (./knowledge/, written by knowledge-setup), read it first: its overview, ideal customer profile, pricing, proof, competitors, voice and instructions are sourced facts. Start from them, cite them, and add what this campaign's sources say on top.
Sources
- Website pages (the primary source). Read them with your own web tools, or ask the user to paste the page text, following
references/website-scraping.md: at most 8 pages from the site's own host, homepage, about, product, pricing, and customers first, never blog posts, careers, legal, or login pages. - Meeting transcripts (Fireflies, Otter, Gong, etc.), product docs, sales materials, case studies, testimonials, competitor notes, and any links or uploads the user shared in the conversation.
- Existing research:
{workspace}/research.md, and the company knowledge folder./knowledge/when it exists. Preserve metadata and facts that still hold; extend rather than overwrite.
Read saved files only when they are not already in the conversation: {workspace}/research/ holds saved website pages (research/website/*.md), transcripts and documents, and {workspace}/notes.md the client's preferences.
Critical Rules
- Extract, don't invent: Only include information present in the sources. Never suggest new ideas or speculate.
- Avoid generic language: Never use "innovative", "cutting-edge", "AI-powered" without explaining the actual mechanism. Be specific about how things work.
- Quantify when possible: Include specific metrics, percentages, dollar amounts, time savings. Numbers make content actionable for outbound.
- Include outbound angles: Every problem, advantage, and lead magnet gets a concrete question or hook for cold email.
- Prioritize by ICP fit: Pick the case studies, lead magnets, and problems most relevant to the primary target audience.
- Write for dual audiences: Scannable by humans AND parseable by AI agents. Use consistent headers and structured formats.
What ships with it
3 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 Changed · -17 lines · -25 tokens per session b0af4b8855b2
- 2mo 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 (4 stars, last pushed 6d ago), licensed MIT. It adds 74 tokens to every session and 1,930 once invoked, about $0.0003 per session on Opus 5.5. 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.
client-research compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| client-researchKen-Technology/cold-email-skills | Skill | 4 | 6d ago | MIT | A | 74 | Claude Code, Codex |
| cold-emailFrontal-so/outbound-skills | Skill | 9 | 1mo ago | MIT | A | 177 | Claude Code, Codex |
| list-buildingFrontal-so/outbound-skills | Skill | 9 | 1mo ago | MIT | A | 190 | Claude Code, Codex |
| claygentFrontal-so/outbound-skills | Skill | 9 | 1mo ago | MIT | A | 131 | Claude Code |
| conditional-logicFrontal-so/outbound-skills | Skill | 9 | 1mo ago | MIT | A | 128 | Claude Code |
| people-enrichmentFrontal-so/outbound-skills | Skill | 9 | 1mo ago | MIT | A | 110 | Claude Code |
| scoringFrontal-so/outbound-skills | Skill | 9 | 1mo ago | MIT | A | 113 | Claude Code |