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 gtmagents/gtm-agents --skill signal-intelgit clone --depth 1 https://github.com/gtmagents/gtm-agentsWrote 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/gtmagents/gtm-agents/signal-intel)<a href="https://agentmods.dev/skills/gtmagents/gtm-agents/signal-intel"><img src="https://agentmods.dev/badge/skills/gtmagents/gtm-agents/signal-intel/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/gtmagents/gtm-agents/signal-intel"><img src="https://agentmods.dev/badge/skills/gtmagents/gtm-agents/signal-intel.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 | $0.00023 | $0.00351 |
| Opus 5 | $0.00012 | $0.00176 |
| Sonnet 5 | $0.00005 | $0.00070 |
| Haiku 4.5 | $0.00002 | $0.00035 |
Grade A, and why
signal-intel 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.
What it actually says
Signal Intelligence Systems Skill
When to Use
- Monitoring account readiness for ABM plays.
- Prioritizing SDR/AE follow-up based on live engagement.
- Coordinating signal-based automations (ads suppression, nurture routing, sales alerts).
Signal Sources
- Intent Platforms – Bombora, 6sense, ZoomInfo (topics, spike scores, recency).
- Product Usage – PQL metrics, feature adoption, seat utilization, idle license detection.
- Engagement – email/web activity, event attendance, community participation, SDR/AE touchpoints.
- Commercial – opp stages, renewal windows, open tickets, expansion likelihood.
- External Events – hiring, funding, tech stack changes, executive moves, news.
Framework
- Normalize identifiers (domain, account ID) across sources.
- Define scoring rules per signal category with decay functions.
- Build alerts/automations (Slack, email, CRM tasks, MAP triggers).
- Feed prioritized lists into plays (target-accounts, plan-plays, monitor-abm).
- Log outcomes to refine weighting and ROI.
Templates
- Signal scoring worksheet (source, weight, freshness, trigger threshold).
- Alert matrix (signal → delivery channel → owner → SLA).
- Data dictionary for dashboards/warehouse models.
Tips
- Combine at least two signal types before triggering high-effort plays.
- Store historical signal snapshots to correlate with pipeline impact.
- Align privacy/compliance flags with marketing automation + CRM suppression rules.
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 · 39 lines · 23 tokens per session scan A 7186acf2b396
signal-intel is a skill published in the GitHub repository gtmagents/gtm-agents (399 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 23 tokens to every session and 351 once invoked, about $0.0001 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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