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.
npx skills add growthenginenowoslawski/coldoutboundskills --skill list-quality-scorecardgit clone --depth 1 https://github.com/growthenginenowoslawski/coldoutboundskillsWrote 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.
[](https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/list-quality-scorecard)<a href="https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/list-quality-scorecard"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/list-quality-scorecard/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.
<a href="https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/list-quality-scorecard"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/list-quality-scorecard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 42 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00069 | $0.01784 |
| Opus 5 | $0.00034 | $0.00892 |
| Sonnet 5 | $0.00014 | $0.00357 |
| Haiku 4.5 | $0.00007 | $0.00178 |
Grade A, and why
list-quality-scorecard 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 13d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- list-quality-scorecard — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
List Quality Scorecard
A CSV of 5,000 leads is not the same as a good list of 5,000 leads. This skill grades your list across 8 dimensions BEFORE you send, catching preventable waste.
Why this exists
The three campaign failure modes cold email runners hit most:
- Bad list — the copy doesn't matter when you're emailing the wrong people
- Unverified emails — bounces burn domain reputation
- ICP drift — you think you're targeting VPs, but the list is mostly Managers
Each of these is catchable before you send, in 5 minutes, for free.
Inputs
A CSV with at minimum these columns:
email— the primary emailfirst_name,last_namejob_titleORtitlecompany_nameORcompanycompany_domain(optional, derived from email if missing)company_industry(optional, used for ICP fit scoring)company_headcount(optional, used for ICP fit scoring)
Output
A markdown scorecard with:
- Letter grade (A+ to F)
- 8 dimension scores (each 0-100)
- Top 5 issues to fix
- Pre-send checklist
Usage
npx tsx scripts/score-list.ts --list=leads.csv --icp-file=client-profile.yaml --out=scorecard.md
Optional --icp-file lets the scorecard compare your list against your declared ICP filters (from /icp-onboarding).
The 8 dimensions
1. Email verification coverage (critical)
- What: % of emails validated via MillionVerifier or equivalent
- Rule: 100% of a cold list must be verified before sending. Unverified emails = bounces = dead domains.
- Score: 100 if all verified, 0 if <50% verified
2. Duplicate email rate
- What: % of duplicate emails in the list
- Rule: <1% acceptable, >5% is a problem
- Score: 100 at 0%, drops linearly
3. Duplicate domain rate
- What: max # of leads from any single domain
- Rule: 1-2 leads per domain ideal. 5+ suggests you're over-indexing on one company.
- Score: 100 if avg <2 per domain, 60 if avg 2-5, 30 if >5
4. Title relevance
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.
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.
- 13d ago First seen · 176 lines · 69 tokens per session scan A 18991a0ee10b
list-quality-scorecard is a skill published in the GitHub repository growthenginenowoslawski/coldoutboundskills (702 stars, last pushed 25d ago), licensed MIT. It adds 69 tokens to every session and 1,784 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 2026-08-30.
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