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 swan-gtm/gtm-skills --skill event-radargit clone --depth 1 https://github.com/swan-gtm/gtm-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/swan-gtm/gtm-skills/event-radar)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/event-radar"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/event-radar/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/swan-gtm/gtm-skills/event-radar"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/event-radar.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00035 | $0.01483 |
| Opus 5 | $0.00017 | $0.00741 |
| Sonnet 5 | $0.00007 | $0.00297 |
| Haiku 4.5 | $0.00003 | $0.00148 |
Grade A, and why
event-radar 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 9d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions
Setup state. Not yet configured for this org. Load the Setup sub-page and walk the user through wiring the event-radar trigger (event-platform WEBHOOK, SCHEDULE + Apify scrape for public attendee lists, or the CRM's attendance workflow) with the right monitored event sources and follow-up sequence before running this play. (After setup is performed, rewrite this paragraph via swan-update-skill to describe the current state — trigger source(s) chosen, monitored events by class (owned / exhibited / industry / competitor), ICP filter, sequence wired, success metric, and last-refreshed date — so future runs see the current configuration without re-checking.)
When this fires
Most commonly WEBHOOK from an event platform (Goldcast, Hopin, Splash, Bizzabo, or a manually-uploaded attendee list), SCHEDULE + Apify (for public attendee lists of competitor / industry events that the user wants to scrape post-event), the CRM's workflow trigger (if attendance is stored in CRM — discover via swan-get-available-triggers), or WEBSITE_VISIT as a proxy for post-event landing-page visits.
The 48-72 hour window after an event is the highest-converting time to reach out.
Step 1 — Classify the event type
The play differs sharply by event class:
| Event class | Attendee signal | Play |
|---|---|---|
| Your owned event (webinar, conference, dinner) | High — they chose you | Follow-up on the topic they came for |
| Industry conference where you exhibited | Medium-high — you met them | Reference the booth interaction |
| Conference attended only — no booth interaction | Medium — same industry, same time | Casual outreach citing the event |
| Competitor's event | Low-medium — in the market | Soft displacement angle, no aggression |
| Partner / adjacent vendor's event | Medium — same buyer pool | Joint-buyer angle |
Step 2 — Pull attendee detail
The trigger payload should include name + email + company + (ideally) session attended or interactions logged. If only company-level data, treat it as a softer signal.
What ships with it
1 file 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.
- 9d ago First seen · 106 lines · 35 tokens per session scan A 3d8234550c1e
event-radar is a skill published in the GitHub repository swan-gtm/gtm-skills (153 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 1,483 once invoked, about $0.0002 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 2026-09-03.
Other skills, from other repositories
signals-hooks
Comprehensive reactive state hooks for integration with flutterhooks.
signals-dart
Advanced reactive state primitives, collections, mixins, and utilities of signalscore.
signals-flutter
Highly optimized Flutter UI bindings and GPU rendering for reactive signals.
signals-migration-6-to-7
Detailed guidelines, patterns, and rules for migrating codebases from signals.dart version 6.x to version 7.x.
signals-preact-dart
Core reactive programming best practices and primitive definitions for preactsignals in Dart.
signals-lint
Standardized compiler diagnostics, static analysis lints, and automated IDE quick-fixes.