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 First-Touch-Inc/firsttouch-agent-skill-packs --skill stalled-deal-reactivationgit clone --depth 1 https://github.com/First-Touch-Inc/firsttouch-agent-skill-packsWrote 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/first-touch-inc/firsttouch-agent-skill-packs/stalled-deal-reactivation)<a href="https://agentmods.dev/skills/first-touch-inc/firsttouch-agent-skill-packs/stalled-deal-reactivation"><img src="https://agentmods.dev/badge/skills/first-touch-inc/firsttouch-agent-skill-packs/stalled-deal-reactivation/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/first-touch-inc/firsttouch-agent-skill-packs/stalled-deal-reactivation"><img src="https://agentmods.dev/badge/skills/first-touch-inc/firsttouch-agent-skill-packs/stalled-deal-reactivation.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 | $0.00117 | $0.02413 |
| Opus 5 | $0.00059 | $0.01207 |
| Sonnet 5 | $0.00023 | $0.00483 |
| Haiku 4.5 | $0.00012 | $0.00241 |
Grade A, and why
stalled-deal-reactivation 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.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Access note: this is a HubSpot-dependent motion. Skip it until HubSpot/CRM data or a FirstTouch-accessible HubSpot list exists.
Stalled Deal Reactivation
Outcome: Find contacts associated to open deals that are not Closed Won/Lost and have had no engagement for 60+ days, then build an owner-approved LinkedIn reactivation queue. AE self-serve path: for a one-time run, use a manually filtered HubSpot contact list of open deals with no engagement for 60+ days. RevOps/admin setup is only needed for recurring workflow automation. If RevOps wants automation, create or document the contact-based HubSpot workflow as an optional setup step. If the connected HubSpot portal or MCP cannot create workflows, output exact RevOps/admin setup steps and do not pretend it was automated.
First-run onboarding gate
Before running this skill for the first time in a workspace, load ../../references/onboarding.md and complete the onboarding questions. Do not proceed until you know: LinkedIn account type (free/basic = no connection notes; recommend 10 connection requests/day and never exceed the FirstTouch max of 20/day; Sales Navigator/Premium = connection notes available; recommend 20 connection requests/day and never exceed the FirstTouch max of 30/day), HubSpot access (MCP, service key/private app token, HubSpot list only, or none), and which play the user wants to run. Recommend high-intent plays before outbound to keep the LinkedIn account healthy. This is a HubSpot-specific play; do not run it unless HubSpot MCP/service-key access is connected.
When to use
- "Reactivate stalled deals" / "Which open deals have gone quiet?"
- A deal is still open but has no email, meeting, note, call, or LinkedIn engagement for 60+ days
- RevOps wants a contact-based HubSpot workflow that automatically catches no-decision risk before quarter-end
- You, or an AE/BDR if you have one, need owner-routed reactivation queues for quiet opportunities
Inputs
- Workflow object: contact-based HubSpot workflow only. Deal-based workflow triggers are unsupported; deal-based triggers are unsupported for this motion. Enroll contacts associated to qualifying deals instead.
- Deal stages in scope: default = contacts associated to deals in open pipeline stages excluding
Closed WonandClosed Lost - Engagement threshold: default = associated deal/contact has no engagement for 60+ days
- Engagement fields: last activity date, last contacted date, last meeting date, notes/calls/emails, and FirstTouch LinkedIn timeline activity where available
- Owner routing: HubSpot deal owner/contact owner and authorized FirstTouch sender
- Workflow action: create list/queue, enroll in FirstTouch flow, or prepare an approval table depending on the connected portal's available workflow actions
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 · 130 lines · 117 tokens per session scan A 0882c16be4eb
stalled-deal-reactivation is a skill published in the GitHub repository First-Touch-Inc/firsttouch-agent-skill-packs (5 stars, last pushed 2mo ago), licensed MIT. It adds 117 tokens to every session and 2,413 once invoked, about $0.0006 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 2026-08-31.
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