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 qualificationgit 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/qualification)<a href="https://agentmods.dev/skills/ken-technology/cold-email-skills/qualification"><img src="https://agentmods.dev/badge/skills/ken-technology/cold-email-skills/qualification.svg" alt="Measured on agentmods" 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 | $0.00055 | $0.00972 |
| Opus 5 | $0.00028 | $0.00486 |
| Sonnet 5 | $0.00011 | $0.00194 |
| Haiku 4.5 | $0.00006 | $0.00097 |
Grade A, and why
qualification 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 7d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Qualification Skill
Write the structured variables for AI prospect qualification. These variables feed any qualification step that scores or filters individual prospects against an ICP.
Output Contract
qualification.md must follow a fixed structure so downstream campaign tooling can parse it reliably. Hard rules this skill must honor:
- Exactly three H2 headings (case-insensitive match):
## Audience Description,## Qualification Criteria,## Disqualification Criteria. - At least 2 of 3 sections must be populated (non-empty). Fewer is a hard parser error.
- No other H2 headings in the file - they'd be silently ignored.
Required Context
- Read
plan.mdfrom the plan folder - Broad ICP definition - Read
search-strategy.mdfrom the plan folder - Search filters already applied. Never restate any of these dimensions in the prompt. - Read
{workspace}/research.md- Client overview, detailed ICP info, competitors ({workspace}= the client campaign workspace, default./cold-email/{slug}/under the current directory)
Core Principles
- Write short, trust the AI - The qualification AI is smart. Give it a brief, plain-language brief and let it reason. A few high-signal lines beat an exhaustive rulebook. No long enumerations of titles, industries, or product names.
- Never repeat the search filters -
search-strategy.mdalready bounds the list (headcount, geography, titles, seniority, industries). Do NOT restate any of it - not in the audience description, not as a criterion. If the filter sets a headcount range, the prompt says nothing about headcount. Qualification only catches what the filters can't see. - Don't over-qualify - Keep it loose. Qualification is a safety net, not a precision filter. When data is incomplete or ambiguous, qualify.
- Disqualification over qualification - Prefer audience_description + a few disqualification_criteria only. Add qualification_criteria only when there's a real positive signal worth confirming.
- Always exclude competitors - The one disqualifier that's always worth including.
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.
- 7d ago First seen · 93 lines · 55 tokens per session scan A 530e82742639
qualification is a skill published in the GitHub repository Ken-Technology/cold-email-skills (3 stars, last pushed 10d ago), licensed MIT. It adds 55 tokens to every session and 972 once invoked, about $0.0003 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.
Other skills, from other repositories
outbound-strategy
Build your own in-house cold email / outbound infrastructure instead of renting Smartlead, Instantly or Lemlist. Use when someone wants to set up self-hosted cold outreach: connecting their own SMTP/IMAP inboxes, sourcing and segmenting B2B leads, writing multi-step sequences, sending at scale with deliverability-safe…
cold-email
Expert cold email strategist for B2B outbound campaigns. Use when the user asks about cold email writing, email sequences, email deliverability, domain warmup, SPF/DKIM/DMARC setup, email personalization, cold email templates, email copywriting frameworks, email compliance (CAN-SPAM, GDPR), bounce management, inbox…
list-building
Expert B2B list building orchestrator for outbound sales campaigns. Use when the user asks about building lead lists, Sales Navigator search, boolean filters, ICP definition, ICP scoring, lead sources, data validation, email verification, list segmentation, Apollo prospecting, Clay Find People, list hygiene…
conditional-logic
Write Clayscript formulas, conditional runs, and credit-saving logic in Clay. Use when the user asks about Clayscript, Clay formulas, conditional runs, saving credits with logic, data manipulation, if/then logic, JavaScript formulas in Clay, or the AI formula generator. Triggers on "Clayscript", "formula"…
deduplicate
Deduplicate prospect lists, merge data from multiple sources, and ensure data quality across columns. Use when user asks about "deduplicate", "duplicates", "remove duplicates", "merge sources", "merge columns", "multiple data sources", "data quality", "clean up list", "duplicate contacts", "Clay auto-dedupe". Do NOT…
competitor-signals
Competitor engagement signal tracking for B2B outbound. Use when the user asks about competitor signals, bad review targeting, G2/Capterra scraping, LinkedIn follower scraping from competitors, battle cards, competitor customer targeting, or churned competitor customers. Do NOT use for tech stack changes broadly (use…