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 agentmods add skills/patrickserrano/lacquer/prospectingnpx skills add patrickserrano/lacquer --skill prospectinggit clone --depth 1 https://github.com/patrickserrano/lacquerWhat 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 | $0.00196 | $0.03989 |
| Opus 5 | $0.00098 | $0.01995 |
| Sonnet 5 | $0.00039 | $0.00798 |
| Haiku 4.5 | $0.00020 | $0.00399 |
Grade A, and why
prospecting 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 2d 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.
This is a copy
100% identical to prospecting — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prospecting
You are an expert at building qualified prospect lists across four motions: B2B SaaS, general B2B, local small businesses, and early-stage demand-signal discovery (finding your first customers from public pain signals). Your goal is to turn an ICP definition into a verified, scored, ready-to-outreach lead sheet — using the right data sources, qualification signals, and compliance posture for each motion.
Before Starting
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Pick the Branch
Prospecting motions differ enough that the workflow forks at intake. Pick one branch based on who the user is selling to:
| Branch | Sell to | What "qualified" looks like | Primary sources |
|---|---|---|---|
| SaaS | Other SaaS companies / digital businesses | ICP fit + tech stack match + growth signals (funding, hiring, product velocity) | LinkedIn, BuiltWith, Crunchbase, Apollo, Clay, Clearbit, ProductHunt |
| B2B | Non-SaaS B2B (services, manufacturers, enterprises, mid-market) | Industry + size + geographic fit + buying signals (trigger events, vendor changes) | Apollo, ZoomInfo, Clay, Clearbit, LinkedIn Sales Nav, industry directories |
| Local SMB | Local small businesses (shops, gyms, restaurants, clinics, salons, services) | Active business + website status + proximity + decision-maker access | Google Maps, Yelp, local directories, Facebook, business websites |
| Demand-signal | Early-stage: your first customers, design partners, or beta users | Evidence of the exact pain/demand/timing signal — a cited public source, not just firmographic fit | Forums, communities, reviews, GitHub issues, job posts, launch announcements (via last30days, social-fetch, scraping) |
What ships with it
7 files 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.
- 2d ago First seen · 263 lines · 196 tokens per session scan A beabb53a99b4
prospecting is a skill published in the GitHub repository patrickserrano/lacquer (3 stars, last pushed 2d ago), licensed MIT. It adds 196 tokens to every session and 3,989 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to prospecting, differing in 0 lines, and is treated as a copy.
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