qualification

qualification is a skill for Claude Code, Codex from Ken-Technology/cold-email-skills. It costs 55 tokens per session (972 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. Also seen: model in frontmatter.

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
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.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.svg" alt="Measured on agentmods" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 972 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 $0.00055 $0.00972
Opus 5 $0.00028 $0.00486
Sonnet 5 $0.00011 $0.00194
Haiku 4.5 $0.00006 $0.00097

Measured 7d ago against content hash 530e82742639, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, 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 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.

qualification/SKILL.md · 93 lines

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

  1. Read plan.md from the plan folder - Broad ICP definition
  2. Read search-strategy.md from the plan folder - Search filters already applied. Never restate any of these dimensions in the prompt.
  3. 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.md already 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.

Read the full file on GitHub · 93 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. 7d 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 (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.

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