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.
Installer avec mon Agent
Copiez cette demande dans votre Agent. Elle contient la page Skill de référence et le manifeste.
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.Votre Agent doit toujours présenter son plan et demander toute confirmation exigée par la politique de sécurité.
Ressources lisibles par les agents
Utilisez ces liens lorsquâun Agent IA, un crawler ou un script a besoin dâun contexte propre au lieu de lire toute la page.
Tester
Utilisation de « cold-email-list-quality ». Illustrative review: a list includes duplicate emails, signals older than 30 days, and prospects outside configured role targets.
RĂ©sultat attendu:
- 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.
Utilisation de « 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.
RĂ©sultat attendu:
- 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.
Audit de sécurité
SûrAll 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.
Facteurs de risque
âïž Commandes externes (26)
đ AccĂšs au systĂšme de fichiers (3)
Partager et citer ce rapport
Partagez le rapport dâĂ©valuation versionnĂ©, le badge neutre, la carte intĂ©grable et les citations. Skillstore prĂ©sente les preuves sans dĂ©cider si ce Skill est sĂ»r.
Copier le lien du rapport
https://skillstore.io/skills/cmj-hub-cold-email-list-quality/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportBadge Markdown
[](https://skillstore.io/skills/cmj-hub-cold-email-list-quality?utm_source=security_passport_badge)Badge 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>Carte intégrable
<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>Citations académiques (APA · BibTeX · CFF)
Citation 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/1Citation 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"
Score Skillstore
Pourquoi ce score Niveau de confiance des preuves: MoyenCe que vous pouvez créer
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.
Essayez ces prompts
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.
Bonnes pratiques
- 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.
Ăviter
- 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.