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 cogni-work/insight-wave --skill lead-generationgit clone --depth 1 https://github.com/cogni-work/insight-waveWrote 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/cogni-work/insight-wave/lead-generation)<a href="https://agentmods.dev/skills/cogni-work/insight-wave/lead-generation"><img src="https://agentmods.dev/badge/skills/cogni-work/insight-wave/lead-generation.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00109 | $0.01770 |
| Opus 5 | $0.00055 | $0.00885 |
| Sonnet 5 | $0.00022 | $0.00354 |
| Haiku 4.5 | $0.00011 | $0.00177 |
Grade A, and why
lead-generation 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead Generation Content
Purpose
Generate conversion-focused content that turns engaged prospects into qualified leads. Lead gen content provides deep value in exchange for contact information. It sits in the consideration stage — the prospect knows they have a problem (from awareness content) and is evaluating approaches.
Prerequisites
- Marketing project with GTM paths configured
- Portfolio propositions and solutions populated for the target market
- Recommended: thought leadership + demand gen content exists (lead gen follows them in the funnel)
Input Parameters
| Parameter | Required | Description |
|---|---|---|
| market | Yes | Market slug |
| gtm_path | Yes | GTM path theme ID |
| format | No | whitepaper, landing-page, email-nurture, webinar-outline, gated-checklist. If omitted, ask |
Workflow
Step 1: Load Context
- Read
marketing-project.json— brand, language, content defaults, CTA style - Read
content-strategy.json— narrative angle (especially possibility_promise + solution_proof) - Load portfolio data heavily:
- Propositions for this market: full IS/DOES/MEANS (the value argument)
- Solutions: implementation phases, pricing tiers (for ROI framing)
- Packages: bundled offerings (for tier-based CTAs)
- Customer profiles: buyer personas, pain points, buying criteria
- Load TIPS data: solution templates, readiness scores (for "what's possible" framing)
Step 2: Generate Content
Delegate to content-writer agent:
Whitepaper (2500-4000 words)
Structure:
- Title page: Title, subtitle, brand, date
- Executive summary (200-300w): Problem → Approach → Key findings → CTA
- The challenge (400-600w): Market problem using TIPS implication data. Data-heavy, persona-specific pain points from portfolio customers.
- The landscape (400-600w): How the market is evolving. Use TIPS trend data + competitor landscape from portfolio.
- The approach (600-800w): Methodology/framework for solving the challenge. Draw from portfolio solution phases WITHOUT naming the product. Position as thought leadership with embedded expertise.
- Evidence & results (400-600w): Case study frameworks, ROI calculations from portfolio solution pricing, industry benchmarks from TIPS claims.
- Implementation roadmap (300-400w): Practical steps, drawn from portfolio solution implementation phases. Generic enough to be useful, specific enough to show expertise.
- Conclusion + CTA (200w): Summary + clear next step (consultation, demo, assessment).
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.
- 3d ago First seen · 140 lines · 109 tokens per session scan A 90f750c43b85
lead-generation is a skill published in the GitHub repository cogni-work/insight-wave (12 stars, last pushed yesterday), licensed Apache-2.0. It adds 109 tokens to every session and 1,770 once invoked, about $0.0005 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 2026-09-04.
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