pricing-reference-frames
78Build Credible Pricing Anchors
Pricing copy can emphasize competitor discounts instead of the buyer's actual costs. This skill selects a credible reference frame and drafts quantified copy with bounded guarantees.
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.
Kopieren Sie diese Anfrage in Ihren Agent. Sie enthält die maßgebliche Skill-Seite und das Manifest.
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.Ihr Agent sollte weiterhin seinen Plan anzeigen und alle von der Sicherheitsrichtlinie verlangten Bestätigungen anfordern.
Verwenden Sie diese Links, wenn ein KI-Agent, Crawler oder Skript sauberen Kontext benötigt, statt die vollständige Seite zu lesen.
„cold-email-list-quality“ wird verwendet. Illustrative review: a list includes duplicate emails, signals older than 30 days, and prospects outside configured role targets.
Erwartetes Ergebnis:
„cold-email-list-quality“ wird verwendet. Illustrative review: ICP rules target revenue leaders at Series A or Series B companies; rows include role accounts and plus-addresses.
Erwartetes Ergebnis:
All 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.
Teile den versionierten Bewertungsbericht, das neutrale Badge, die Einbettungskarte und Zitate. Skillstore berichtet Nachweise, ohne zu entscheiden, ob dieser Skill sicher ist.
https://skillstore.io/skills/cmj-hub-cold-email-list-quality/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/cmj-hub-cold-email-list-quality?utm_source=security_passport_badge)<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><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>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/1@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}
}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"
Review an imported CSV or JSONL list for duplicates, address concerns, and records outside campaign requirements.
Review signal age, role fit, exclusions, and company stage before refreshing the weekly campaign list.
Compare supplied prospects with ideal customer profile rules and prioritize changes to targeting or list sourcing.
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.
Autor
cmj-hubLizenz
MIT
Skillstore-Revision
r1
Versionshinweis
Der Autor hat keine Version angegeben.
Ref.
423e93f4118301bf3ae5fc40f25942fc4c591e60
Aktualität der Wartung
3.10.2026
Nutzung
0 Downloads · 0 Aufrufe
Dateistruktur
📄 SKILL.md
Build Credible Pricing Anchors
Pricing copy can emphasize competitor discounts instead of the buyer's actual costs. This skill selects a credible reference frame and drafts quantified copy with bounded guarantees.
Record a Single-URL Indexability Check
A page needs fetchability and listing evidence before its citation potential can be assessed. This skill organizes a single-URL checklist covering status, robots, sitemap, and scoring validation.
Craft Signal-Anchored Cold Emails
Generic outreach is easy to ignore and difficult to validate. This skill turns a recent public signal into concise, specific outreach with a binary call to action.
Build Evidence-Based Pain Signal Profiles
Broad customer segments and generic messaging make operational pain difficult to identify. This skill guides structured research linking recent signals, pain, timing, roles, and recipient vocabulary.
Choose a Value Metric That Scales
Many B2B companies charge by a unit that does not track customer success, creating margin leakage, gaming, or expansion limits. This skill compares pricing units against four criteria and recommends a defensible hold or metric shift.
Write Stronger Founder LinkedIn Posts
Founders often have useful experience but struggle to turn it into specific, credible LinkedIn posts. This skill structures one post around a clear pillar, hook, receipt, and founder voice.
Unordentliche Daten mit einer Pipeline bereinigen
von zhangchenlai-dev
Unordentliche Datensätze verlangsamen Analysen und führen zu unzuverlässigen Ergebnissen. Diese Skill hilft Claude, Codex und Claude Code dabei, Bereinigungsschritte für Deduplizierung, fehlende Werte, Formatierung und Anomalieprüfungen zu planen.
Daten-Arrays mit wiederverwendbaren Operationen transformieren
von ArtemisAI
Große Datensatz-Arrays sind in KI-Workflows schwer zu bereinigen, zu sortieren und zusammenzufassen. Dieser Skill bietet wiederverwendbare JavaScript-Operationen für gängige Transformationen und kompakte Verarbeitungszusammenfassungen.
Daten mit SQL und pandas analysieren
von shubhamsaboo
Datenarbeit erfordert oft klare Abfragen, wiederholbare Transformationen und eine sorgfältige Interpretation. Diese Skill unterstützt Workflows für SQL, pandas, Statistik und Datenbereinigung.
Inspect Collections for Safe Deduplication
von srinitude
Duplicate cleanup can remove unique information when identity rules are unclear. This skill creates evidence-rich reports and gates every mutation behind explicit review.
Standardize Electronics BOM Cleanup
von nexaiguy
Inconsistent BOM exports create duplicate orders and incomplete procurement records. This guide defines cleanup rules for column mapping, matching-part merges, reference formatting, and missing-data review.
CSV-Dateien mit Datenbereinigungs-Workflows verarbeiten
von CuriousLearner
CSV-Dateien enthalten häufig inkonsistente Formate, fehlende Werte, Duplikate und große Datensätze. Dieser Skill bietet praktische Workflows zum Parsen, Bereinigen, Transformieren, Zusammenführen und Analysieren von CSV-Daten.