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 webinar-to-qualified-pipelinegit 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/webinar-to-qualified-pipeline)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/webinar-to-qualified-pipeline"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/webinar-to-qualified-pipeline/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/webinar-to-qualified-pipeline"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/webinar-to-qualified-pipeline.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 | $0.00074 | $0.01155 |
| Opus 5 | $0.00037 | $0.00577 |
| Sonnet 5 | $0.00015 | $0.00231 |
| Haiku 4.5 | $0.00007 | $0.00115 |
Grade A, and why
webinar-to-qualified-pipeline 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use this when a webinar has produced names but the revenue team cannot tell who deserves sales attention, useful follow-up, or no action. It turns verified engagement and fit into a controlled pipeline process.
Define the commercial job
Write one sentence that names the audience, the problem taught, and the next buying step. A webinar for awareness, customer education, partner enablement, and opportunity acceleration cannot share one qualification rule.
Define the conversion ladder:
- registration;
- attended live, watched replay, or no-show;
- meaningful engagement;
- sales review accepted;
- meeting booked;
- qualified opportunity created.
Keep every rung separate. Registration is a content conversion, not pipeline. Attendance still does not prove fit, authority, a current problem, or willingness to buy.
Reconcile identities and states
Create one record per person and preserve source, campaign, event, answers, permission, company, role, and existing relationship. Resolve duplicates conservatively. Uncertain identity matches go to review instead of merging.
Assign one current state using references/lifecycle-states-and-suppression.md. A later, harder state overrules an earlier one. A confirmed meeting ends booking nurture. Customers and open opportunities route to their existing owner.
Score fit and intent separately
Do not let watch time rescue a poor-fit account. Score three dimensions:
- Fit, 0–40: account, persona, market, and use-case match.
- Engagement, 0–30: attendance depth, replay, questions, polls, and calls to action.
- Buying intent, 0–30: stated problem, decision-stage question, high-intent page visit, reply, or meeting request.
Use references/qualification-scorecard.md for the rubric and these starting bands:
- 0–24: record only or low-frequency nurture;
- 25–49: relevant nurture, no sales task;
- 50–69: human sales review;
- 70–100: priority sales review and handoff.
A score of 70 qualifies for handoff only when Fit is at least 20 and Buying Intent at least 10. Booked meetings move to sales. Suppression and existing relationships override scoring.
What ships with it
4 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.
- 9d ago First seen · 96 lines · 74 tokens per session scan A 5cf34a67d65a
webinar-to-qualified-pipeline is a skill published in the GitHub repository swan-gtm/gtm-skills (150 stars, last pushed 2d ago), licensed MIT. It adds 74 tokens to every session and 1,155 once invoked, about $0.0004 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.
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