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 icp-prompt-buildergit 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/icp-prompt-builder)<a href="https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/icp-prompt-builder"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/icp-prompt-builder/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/icp-prompt-builder"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/icp-prompt-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 134 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]
- medium Excessive Agency · line 142 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00101 | $0.02181 |
| Opus 5.5 | $0.00040 | $0.00872 |
| Sonnet 5.5 | $0.00020 | $0.00436 |
| Haiku 4.5 | $0.00010 | $0.00218 |
Grade A, and why
icp-prompt-builder 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 1mo 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:
- icp-prompt-builder — 100% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ICP Prompt Builder
Before you pay to pull 5,000 companies, tune a qualification prompt on 10-50 of them. This skill walks you through the iterative loop.
Why this exists
List-builder skills (DiscoLike, Blitz, Prospeo, Google Maps) return COMPANIES, but they don't know whether those companies match your ICP. If your list-builder returns 5,000 companies and 80% are wrong fits, you'll waste money enriching them for emails that go nowhere.
The fix: build an AI qualification prompt BEFORE scaling. Pull 10 companies, have the prompt score them, compare to your judgment, refine, repeat. Once the prompt agrees with you 2 rounds in a row with zero corrections, lock it in and apply it at scale.
Always uses Task sub-agents (no API key)
This skill runs entirely inside Claude Code via the Task tool. No Anthropic SDK calls, no OpenAI calls — Claude Code does the scoring itself. This is intentional:
- No extra API spend. Uses your Claude Code plan.
- No key management. Works out of the box.
- Scaleable within reason. For 20-100 evaluations, parallel Task sub-agents batch 10-20 companies per agent.
At very large scale (5,000+ companies per batch), you may want to export the tuned prompt and run it through the OpenAI / Anthropic API with parallelism for speed. But TUNING happens inside Claude Code.
The loop (8 steps)
Step 1 — Gather ICP context
Claude asks the user (or reads client-profile.yaml from /icp-onboarding):
- Website of the client selling (to scrape for context)
- Who IS a good customer? What makes them a good fit?
- Who is NOT a good customer? What disqualifies them?
- Any specific signals? (B2B only, revenue range, tech stack, hiring status, recent fundraise, etc.)
- Any HARD disqualifiers? (competitor domains, existing customer domains, certain industries/geographies)
Step 2 — Select 10 test companies
Pull 10 companies from the list-builder output:
- Mix likely-good and likely-bad fits
- Variety in industry, size, location
- Each company needs at minimum:
domain, company_name, industry, headcount, description - Richer fields (Clay-derived: Business Type, Scale Scope, Revenue) make scoring better
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.
- 1mo ago Changed 2eac4c62b470
- 2mo ago First seen · 206 lines · 101 tokens per session scan A eaec0306b7a2
icp-prompt-builder is a skill published in the GitHub repository growthenginenowoslawski/coldoutboundskills (802 stars, last pushed 1mo ago), licensed MIT. It adds 101 tokens to every session and 2,181 once invoked, about $0.0004 per session on Opus 5.5. 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.
icp-prompt-builder compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| icp-prompt-buildergrowthenginenowoslawski/coldoutboundskills | Skill | 802 | 1mo ago | MIT | A | 101 | Claude Code, Codex |
| llm-app-patternsdavila7/claude-code-templates | Skill | 33k | today | MIT | A | 54 | Claude Code, Codex |
| prompt-engineerJeffallan/claude-skills | Skill | 12k | 7d ago | MIT | A | 93 | Claude Code |
| prompt-optimizationlangwatch/langwatch | Skill | 5.0k | yesterday | Apache-2.0 | A | 105 | Claude Code, Codex |
| omh-model-optimizationrlaope/oh-my-hermes | Skill | 5.2k | today | MIT | A | 84 | Claude Code, Codex |
| ideogram4digitalsamba/claude-code-video-toolkit | Skill | 2.5k | today | MIT | A | 99 | Claude Code |
| prompt-library-for-startupsaws/agent-toolkit-for-aws | Skill | 3.4k | yesterday | Apache-2.0 | A | 228 | Claude Code |