cold-email-list-quality
Score and Clean Prospect Lists
Duplicates, stale signals, and targeting mismatches waste outreach capacity. This skill guides CSV or JSONL list reviews with a weighted rubric, removal reasons, and prioritized cleanup recommendations.
Установить с помощью моего Агента
Скопируйте этот запрос в своего Агента. Он содержит каноническую страницу Skill и манифест.
Review the Skillstore skill "cold-email-list-quality" from https://skillstore.io/skills/cmj-hub-cold-email-list-quality.md and its manifest at https://skillstore.io/api/skills/cmj-hub-cold-email-list-quality/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Ваш Агент по-прежнему должен показать план и запросить все подтверждения, требуемые политикой безопасности.
Ресурсы для AI-агентов
Используйте эти ссылки, когда AI-агенту, crawler или script нужен чистый контекст вместо полной страницы.
Протестировать
Использование «cold-email-list-quality». Illustrative review: a list includes duplicate emails, signals older than 30 days, and prospects outside configured role targets.
Ожидаемый результат:
- Illustrative score: 72/100. Deduplication: 16/20; role fit: 18/25; freshness: 10/20; address heuristics: 12/15; exclusions: 8/10; company stage: 8/10.
- Keep the oldest record for each duplicate email. Review near-duplicates manually.
- Refresh stale signals and review prospects outside role targets before import. Mailbox deliverability remains unverified.
Использование «cold-email-list-quality». Illustrative review: ICP rules target revenue leaders at Series A or Series B companies; rows include role accounts and plus-addresses.
Ожидаемый результат:
- Flag role-account addresses for removal under the documented B2B heuristic.
- Warn on plus-addresses without claiming they are invalid mailboxes.
- Compare inferred funding stages and revenue roles with the configured targets. Report uncertain company stages for review.
Аудит безопасности
БезопасноAll 31 static findings are false positives: Markdown delimiters, fixed repository-relative paths, and list-quality terminology do not demonstrate the detected threats. No evidence found of credential theft, data exfiltration, prompt injection, or reconnaissance in the reviewed skill. The documented Python script is absent, so its execution safety cannot be assessed.
Факторы риска
⚙️ Внешние команды (26)
📁 Доступ к файловой системе (3)
Поделиться и цитировать этот отчет
Делитесь версионным отчетом об оценке, нейтральным значком, встраиваемой карточкой и цитатами. Skillstore публикует доказательства, не решая, безопасен ли этот Skill.
Копировать ссылку на отчёт
https://skillstore.io/skills/cmj-hub-cold-email-list-quality/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportЗначок Markdown
[](https://skillstore.io/skills/cmj-hub-cold-email-list-quality?utm_source=security_passport_badge)Значок HTML
<a href="https://skillstore.io/skills/cmj-hub-cold-email-list-quality?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/cmj-hub-cold-email-list-quality/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Встраиваемая карточка
<iframe src="https://skillstore.io/embed/skills/cmj-hub-cold-email-list-quality.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Академические ссылки (APA · BibTeX · CFF)
Цитата APA
cmj-hub. (2026). cold-email-list-quality security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/cmj-hub-cold-email-list-quality/audits/1Цитата BibTeX
@techreport{cmj-hub-cmj-hub-cold-email-list-quality-2026,
author = {cmj-hub},
title = {cold-email-list-quality security audit report (audit version 1)},
institution = {Skillstore},
year = {2026},
number = {1},
url = {https://skillstore.io/skills/cmj-hub-cold-email-list-quality/audits/1},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "cold-email-list-quality security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
- name: "cmj-hub"
date-released: "2026-10-03"
url: "https://skillstore.io/skills/cmj-hub-cold-email-list-quality/audits/1"
identifiers:
- type: other
value: "skillstore:cmj-hub-cold-email-list-quality:audit:1"
description: "Skillstore immutable audit report identifier"
Оценка Skillstore
Почему такая оценка Достоверность доказательств: СреднийЧто вы можете построить
Prepare a New Prospect List
Review an imported CSV or JSONL list for duplicates, address concerns, and records outside campaign requirements.
Refresh Weekly Outreach Data
Review signal age, role fit, exclusions, and company stage before refreshing the weekly campaign list.
Audit ICP Alignment
Compare supplied prospects with ideal customer profile rules and prioritize changes to targeting or list sourcing.
Попробуйте эти промпты
Review prospects.csv using the documented quality rubric. Report axis scores, removal candidates, and top fixes. State missing fields and avoid assuming mailbox deliverability.
Review prospects.csv for duplicate emails, LinkedIn URLs, and person-company matches. Keep the oldest email record and newest LinkedIn signal. Flag near-duplicates for review.
Score prospects.csv against brand-config.json. Check roles, exclusions, signal dates, address heuristics, and inferred company stages. Explain assumptions and separate warnings from removal recommendations.
Audit prospects.jsonl using brand-config.json and supplied warm-up status. Report scores, cleanup priorities, and send-volume arithmetic. Preserve the original. Write reviewed cleaned and removed CSV files.
Лучшие практики
- Provide current ICP configuration, dated signals, and complete prospect fields; identify missing information before accepting scores.
- Preserve the original list and review removal reasons and output destinations before writing cleaned files.
- Confirm mailbox deliverability separately and refresh stale signals before campaign import.
Избегать
- Treating a high quality score as proof of deliverability or permission to contact prospects.
- Executing the documented Python example when the referenced scoring script is absent.
- Automatically deleting near-duplicates or treating plus-address warnings as proof of invalid mailboxes.