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qualification

qualification is a skill for Claude Code, Codex from Ken-Technology/cold-email-skills. It costs 60 tokens per session (1,390 once invoked), scanned A, original, MIT.

A campaign-planning skill that writes the instructions an AI uses to decide whether individual prospects fit a target customer profile. It produces audience, qualification, and disqualification guidance in a fixed format.

In plain words
What is it for?
Use it when setting up AI prospect qualification for a cold-email campaign. It helps define who should qualify, who should be rejected, and optionally which extra conditions matter.
Why use it?
It removes the need to write and organize these screening instructions by hand. The fixed format also helps campaign tools read them correctly.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 4repo changed 9d ago A scan 60 tokens original MIT

Good fit Use it when setting up AI prospect qualification for a cold-email campaign. It helps define who should qualify, who should be rejected, and optionally which extra conditions matter.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ken-technology/cold-email-skills/qualification
View source ↗ Ken-Technology/cold-email-skills ken.so
Install

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.

Any agent
npx skills add Ken-Technology/cold-email-skills --skill qualification
Clone the repo
git clone --depth 1 https://github.com/Ken-Technology/cold-email-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for qualification

README.md
[![agentmods](https://agentmods.dev/badge/skills/ken-technology/cold-email-skills/qualification/github.svg)](https://agentmods.dev/skills/ken-technology/cold-email-skills/qualification)
Your own site
<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/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.

agentmods 80×15 button for qualification

Your own site · 80×15
<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="Reviewed on agentmods" width="80" height="20"></a>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,390 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00060 $0.01390
Opus 5.5 $0.00024 $0.00556
Sonnet 5.5 $0.00012 $0.00278
Haiku 4.5 $0.00006 $0.00139

Measured 9d ago against content hash 01074b6f560a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 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.

qualification/SKILL.md · 99 lines

How it starts

The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Qualification Skill

Turn a campaign plan's qualify/disqualify rules into the variables an AI qualifier runs on every prospect: an audience description, disqualification criteria, and (rarely) qualification criteria. They go in qualification.md at the root of the campaign workspace (./cold-email/{slug}/), ready for any qualification step: an AI column in Clay or a spreadsheet, or any LLM.

Inputs

  • The plan's broad ICP and its qualify/disqualify rules.
  • The search filters already applied (search-strategy.md in the campaign workspace). They tell you what NOT to restate.
  • The research (research.md and its company context) for competitors and ICP nuances, and the company knowledge folder (./knowledge/) when it exists: its competitors/ files and who the ideal customer profile says is not a fit.
  • A sample of sourced leads, when available, to see real edge cases.

Use what the conversation already holds. Read only what is missing: plan.md, search-strategy.md and research.md in the campaign workspace (default ./cold-email/{slug}/ under the current directory).

What the qualifier can see

The qualifier sees ONLY:

  • LinkedIn profile: title, company, location, previous roles, education, skills, summary.
  • Company data: industry, headcount, HQ, description.
  • Website metadata: page title and meta description only.

It does NOT see full site content, tech stack, news, funding, social posts, press, events, or any time-sensitive signal. Every criterion must be checkable against the data above. Rewrite or drop any rule that depends on something else.

Core Principles

  • Write short, trust the AI - Give it a short, plain-language brief and let it reason. A few high-signal lines beat an exhaustive rulebook. No long lists of titles, industries, or product names.
  • Never repeat the search filters - The filters already bound the list (headcount, geography, titles, seniority, industries). Do not restate any of it, not in the audience description and not as a criterion. Qualification only catches what the filters can't see.
  • Don't over-qualify - Qualification is a safety net, not a precision filter. When data is incomplete or ambiguous, qualify.
  • Disqualification over qualification - Prefer audience description + a few disqualifiers. Add qualification criteria only for a real positive signal worth confirming.
  • Always exclude competitors - The one disqualifier that is always worth including.

Read the full file on GitHub · 99 lines

Files

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.

Changes

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.

  1. 9d ago Changed · +6 lines · +5 tokens per session 01074b6f560a
  2. 2mo ago First seen · 93 lines · 55 tokens per session scan A 530e82742639

Subscribe to this mod's changes

qualification is a skill published in the GitHub repository Ken-Technology/cold-email-skills (4 stars, last pushed 6d ago), licensed MIT. It adds 60 tokens to every session and 1,390 once invoked, about $0.0002 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.

Building agentsClaude CodeMarketing and SEOagent-skillsai-agentscodexcold-emailoutbound
Related

qualification compared with skills from other repositories

qualification next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
qualificationKen-Technology/cold-email-skillsSkill46d agoMITA60Claude Code, Codex
cold-emailFrontal-so/outbound-skillsSkill91mo agoMITA177Claude Code, Codex
list-buildingFrontal-so/outbound-skillsSkill91mo agoMITA190Claude Code, Codex
claygentFrontal-so/outbound-skillsSkill91mo agoMITA131Claude Code
conditional-logicFrontal-so/outbound-skillsSkill91mo agoMITA128Claude Code
people-enrichmentFrontal-so/outbound-skillsSkill91mo agoMITA110Claude Code
scoringFrontal-so/outbound-skillsSkill91mo agoMITA113Claude Code