cold-email-list-quality

cold-email-list-quality is a skill for Claude Code from cmj-hub/claude-cold-email. It costs 88 tokens per session (1,555 once invoked), scanned A, original, MIT.

A checklist and scoring tool for cleaning prospect lists used for unsolicited business email. It checks duplicate rows, job-role fit, signal age, email format, exclusions, and company stage.

In plain words
What is it for?
Use it to review CSV or JSONL contact lists, assign a 0–100 quality score, identify rows to remove, and get repair suggestions.
Why use it?
It helps find weak or repeated contacts before they enter a campaign. This reduces wasted outreach caused by outdated, unsuitable, or invalid prospects.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is python3 ../../scripts/score_list.py \.

Part of the cold-email plugin — 12 skills, 2 agents shipped together

Good fit Use it to review CSV or JSONL contact lists, assign a 0–100 quality score, identify rows to remove, and get repair suggestions.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/cmj-hub/claude-cold-email
agentmods
npx agentmods add skills/cmj-hub/claude-cold-email/cold-email-list-quality

Made for: Claude Code.

Or install cold-email, the plugin that ships this one along with the rest of its 12 skills, 2 agents.

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 cold-email-list-quality

README.md
[![agentmods](https://agentmods.dev/badge/skills/cmj-hub/claude-cold-email/cold-email-list-quality/github.svg)](https://agentmods.dev/skills/cmj-hub/claude-cold-email/cold-email-list-quality)
Your own site
<a href="https://agentmods.dev/skills/cmj-hub/claude-cold-email/cold-email-list-quality"><img src="https://agentmods.dev/badge/skills/cmj-hub/claude-cold-email/cold-email-list-quality/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 cold-email-list-quality

Your own site · 80×15
<a href="https://agentmods.dev/skills/cmj-hub/claude-cold-email/cold-email-list-quality"><img src="https://agentmods.dev/badge/skills/cmj-hub/claude-cold-email/cold-email-list-quality.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,555 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 $0.00088 $0.01555
Opus 5 $0.00044 $0.00777
Sonnet 5 $0.00018 $0.00311
Haiku 4.5 $0.00009 $0.00155

Measured 2d ago against content hash c3c4c49b8eea, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

cold-email-list-quality 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 2d 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.

skills/cold-email-list-quality/SKILL.md · 161 lines

How it starts

The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cold Email List Quality — list scoring + dedup

Run before any campaign. Bad lists kill reply rates more than bad copy. This sub-skill scores the list across 6 axes, returns the rows to remove, and surfaces fix recommendations.

Activation

Loaded by:

  • cold-email-weekly-rhythm — Monday's list refresh
  • User invocation: "Score my list", "Check list quality", "Clean my prospect list"

Inputs

The skill accepts:

  • CSV with at minimum: email, optional first_name, last_name, role, company, signal, signal_date, linkedin_url
  • JSONL with same fields

If brand-config.json is loaded, the skill cross-references icp.segment, icp.role_targets, icp.exclusion_criteria, and psp.signal_anchors for scoring.

Scoring (6 axes, 100 total)

Axis Max What it catches
Dedup 20 Exact-match emails, near-duplicate same-company-same-person rows
Role-fit 25 Role title matches brand-config.icp.role_targets or known equivalents
Signal freshness 20 Signal age — fresh (≤14d) > recent (15-30d) > stale (>30d)
Email validity 15 Heuristic checks — RFC-shaped, no plus-extensions for B2B, no free-email domains, no role-account emails (info@, sales@)
Exclusion match 10 Row matches any brand-config.icp.exclusion_criteria → fail
Company-stage match 10 Company stage (from signal or heuristic) matches ICP segment

Output

# List Quality Score — <file>

## Overall: <0-100>/100

| Axis | Score | Issues |
|---|---|---|
| Dedup | <0-20>/20 | <N> duplicate rows |
| Role-fit | <0-25>/25 | <N> rows outside ICP role targets |
| Signal freshness | <0-20>/20 | <N> stale signals (>30d) |
| Email validity | <0-15>/15 | <N> invalid / free-email / role-account |
| Exclusion match | <0-10>/10 | <N> rows hit exclusion criteria |
| Company-stage match | <0-10>/10 | <N> wrong-stage companies |

## Rows to remove (<N> total)

| Row | Email | Reason |
|---|---|---|
| 12 | [email protected] | Free-email domain (B2B) |
| 14 | [email protected] | Role-account email |
| 22 | [email protected] (Engineering Manager) | Role outside ICP (target: VP+) |
| 27 | [email protected] | Signal stale (45 days) |
| ... |

## Fix recommendations (in order)

1. Remove the 12 free-email + role-account rows (immediate)
2. Re-pull signals for the 8 stale rows (today)
3. Tighten role-fit list — 14 rows are "Engineering Manager" / "Director"
   while ICP targets VP+. Consider adding "Director" if the ICP has
   shifted, or excluding these rows.
4. Run `cold-email-deliverability` on the sending domain before this
   list ships.

## Send-volume recommendation

With cleaning, the deliverable list is: <N - removed> rows.

Given warm-up state (`<warm_up_status>`), recommended weekly send
volume: <X> per day across <M> mailboxes = <X*M> per day = <X*M*5>
per week.

## Send the cleaned list

The skill writes `<file>.cleaned.csv` and `<file>.removed.csv` to the
project root. Operator can review before importing into Smartlead /
Instantly / etc.

Read the full file on GitHub · 161 lines

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. 2d ago Changed · -1 lines c3c4c49b8eea
  2. 11d ago First seen · 162 lines · 88 tokens per session scan A 7f4bbe8d08e4

Subscribe to this mod's changes

cold-email-list-quality is a skill published in the GitHub repository cmj-hub/claude-cold-email (2 stars, last pushed 2d ago), licensed MIT. It adds 88 tokens to every session and 1,555 once invoked, about $0.0004 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.