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 Frontal-so/outbound-skills --skill buying-signals-6git clone --depth 1 https://github.com/Frontal-so/outbound-skillsWrote 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/frontal-so/outbound-skills/buying-signals-6)<a href="https://agentmods.dev/skills/frontal-so/outbound-skills/buying-signals-6"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/buying-signals-6/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/frontal-so/outbound-skills/buying-signals-6"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/buying-signals-6.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00056 | $0.00706 |
| Opus 5 | $0.00028 | $0.00353 |
| Sonnet 5 | $0.00011 | $0.00141 |
| Haiku 4.5 | $0.00006 | $0.00071 |
Grade A, and why
buying-signals-6 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 12d 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
98% identical to buying-signals-6 — 4 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
6 Buying Signals (Ranked by Purchase Correlation)
1. Former Customers & Alumni Users (Highest Correlation)
Why it works:
- Trust already established + known playbook
- Faster proof of value
Query: Previous users of your product at new companies
Outreach timing: Immediately upon detection
2. New Leadership ≤90 days
Why it works:
- Mandate for early wins
- Vendor amnesty period
- Budget air cover for new initiatives
Query: LinkedIn job changes, press releases
Outreach timing: Days 14-45 (peak engagement window)
3. High-Intent Website & Content
Why it works:
- BOFU pages: pricing, competitor comparisons, demo, integrations
- Shows active evaluation
Query: Website visitor tracking, content downloads
Outreach timing: Within 24-48 hours (highest intent signal)
Reply rate: 25-30% (they know you)
4. Tech Stack Change
Why it works:
- Active change project indicates openness
- Fresh pain from transition
- New gaps in workflow
Query: BuiltWith, job postings mentioning new tools
Outreach timing: 1-2 weeks after detection
5. Expansion (Raise, New Region/Product)
Why it works:
- Board targets create urgency
- Scale pain emerges
- Standardization moment
Query: Crunchbase, press releases, job postings
Outreach timing: 2-4 weeks after announcement
6. Hiring or Downsizing
Why it works:
- Hiring = ramp pressure, need efficiency
- Downsizing = do-more-with-less mandate
Query: LinkedIn company growth, layoff news
Outreach timing: 1-2 weeks after pattern detected
Signal Performance Benchmarks
| Outreach Type | Reply Rate |
|---|---|
| Cold outreach | 6-8% |
| Signal-based | 18-22% |
| Multi-signal stacked | 35-40% |
Key insight: Signal-based outreach = 3-4x higher contract values
Combines with
| Skill | Why |
|---|---|
clay-buying-signals-5 |
Implement signals in Clay workflows |
gtm-plays-11 |
Match signals to specific GTM plays |
cold-email-4-sequence |
Build sequences around each signal |
bridgebound-in-market-20 |
Deep-dive on in-market triggers |
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.
- 12d ago First seen · 124 lines · 56 tokens per session scan A c93c67ed434b
buying-signals-6 is a skill published in the GitHub repository Frontal-so/outbound-skills (5 stars, last pushed 2mo ago), licensed MIT. It adds 56 tokens to every session and 706 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to buying-signals-6, differing in 4 lines, and is treated as a copy.
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