Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.
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 gooseworks-ai/goose-skills --skill email-lifecyclegit clone --depth 1 https://github.com/gooseworks-ai/goose-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/gooseworks-ai/goose-skills/email-lifecycle)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/email-lifecycle"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/email-lifecycle/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/gooseworks-ai/goose-skills/email-lifecycle"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/email-lifecycle.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 | $0.00148 | $0.04096 |
| Opus 5.5 | $0.00059 | $0.01638 |
| Sonnet 5.5 | $0.00030 | $0.00819 |
| Haiku 4.5 | $0.00015 | $0.00410 |
Grade A, and why
email-lifecycle 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 4d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
email-lifecycle
One marketer want: "Cart and welcome emails make money while I sleep — mine do not exist." The playbook drafts and stages a lifecycle program; the marketer loads it into their own tool and presses send.
What you get
- Deliverability and list report — every plumbing item green / red / unknown, each marked verified (the agent saw it), from you or unknown. Never a green the agent did not see. Red and unknown items come with the exact fix and who does it.
- Flow pack — the flows you asked for, or else the top two this business can load today (a third is offered), each a build sheet in your tool's own terms: trigger, filters, exit, re-entry, consent per market, priority and suppressions, timing, and every message finished, plus its goal metric, its test, a holdout where one fits, and the result it should beat. Each flow is marked ready to load or not ready, with the blocker in plain words ("waiting on your answer about returns", "needs your app to tell the email tool who installed", "your current plan can't run this — here are the options").
- Segments, priority and cadence — segment definitions in the company's own terms (clicks, orders, activity — not opens), the flow priority map and frequency cap, the proposed send cadence.
- This week's broadcasts and the month's calendar — broadcasts finished and ready to schedule (email; SMS only where consent exists and the moment is high-intent); the calendar as one table of dates and ideas.
- Proposals awaiting a yes — offer depth with margin math, cadence, sunset slice, tool or plan changes, a tracking plan for missing events, any high-stakes send.
Before you start
- Setup first: do the
marketing-guideskill (../marketing-guide/SKILL.md) §1–2 (connect, brand, brain read) before anything else; the job line is "build your email program";get_startedalso takeswants: "more"; groups to load: files, campaigns, media, automation, brand. Incident mode (step 2) runs its pause list before the brain read. - Pick the mode (
references/modes-and-incidents.md): build, weekly, monthly, seasonal or incident. Incident first: the first reply is the "pause now" list as click-by-click steps for the marketer — before any brain read, intake or audit. Otherwise do only the work the asked outcome needs and say in one line what you are not doing this run. - Read the brand brain. Brain chapters: 2 "What we sell" (prices, offers, policies), 5 "Who we sell to", 11 "How we sound", 15 "How we work together", 17 "Accounts and tools" (the email tool), 18 "How we count results", 20 "Our plan";
gooseworks:brain_openfor full product records. Fallback path:brand_readsectionssummary,kit,products,onboarding,learnings, and full product records (product_ids) for products the flows will feature. Load theclaims-gateskill (../claims-gate/SKILL.md) and read the contract only; the scoped sign-off, if needed, comes in intake message 2. The standing first-order offer and brand-wide policies come from theStanding offer:, anyPolicy:and earlier[lifecycle …]facts (else the Brand record, read withfile_read); never from search snippets. For a message signed by a person, read their voice card if one exists (thevoice-cardskill (../voice-card/SKILL.md), read only); if none, write in the brand voice, say the note isn't yet in their own voice, and offer to build the card later. - Load the last run, then read what the program already knows. Run the Start steps of the
run-memoryskill (../run-memory/SKILL.md) withreferences/run-memory.md(incident mode: after the pause list) — steps 1–2 now: the newest record across the email jobs gives last run's numbers with their windows and its open recommendations ("add a second cart email"), so intake message 1 asks for the export that covers them; steps 3–4 inside step 1's audit, once the exports are in: each recommendation checked done / not done / unknown from the flows list, a test email or the marketer's word, and judged against its baseline when a settled window exists. Thengooseworks:file_readlifecycle/program.md(flows live, each flow's hypothesis and last result, segments, cadence);gooseworks:file_listreports/performance/and read the latest weekly read's email rows;gooseworks:campaign_readto list the brand's campaigns, then read each active one in full for its email/SMS rows and hand-offs; the latestsearch/fixes/file's "For your email program — review requests" section (a review-request brief);content/newsletter/for make-content's next issue;Graphic ready:lines under this playbook's own header-art requests inlifecycle/flows/. The marketer's email-tool connector, when listed, is read only (references/intake.mdQ2). - Ask only what is missing, in two short messages (
references/intake.mdhas the wording). Message 1 (≤ 8 questions, prefilled with best guesses; skip what the brand type or a campaign brief already settles): the email tool and plan first, unless the brain names it (the guide's rule "The marketer's own tools": no tool → options for their type; its connector listed → read it and drop the questions it answers; not listed → one ask to connect, then the questions —references/intake.mdQ2), what counts as the win, how the list was collected and consent per channel, markets, the standing offer if the brain doesn't hold it, and — optional, as click-by-click steps — the flows list and last 90 days' report from their tool, the "original message" text of one recent campaign they received from their own list, and the spam-rate chart if they use Google's sender dashboard. Message 2 comes after step 2, only for facts the chosen flows use (≤ 6), prefilled from the brand's own site and labelled "from your site — confirm". Never guess consent, discount depth, prices, stock, shipping or return promises, renewal terms, trial length, existing event names, reward amounts or time zones. - Hard stops. A purchased, scraped or no-consent list, or customers imported from marketplace orders: stop for those contacts, say why in one line, offer the re-permission route. A list not mailed in 6+ months (a waitlist: 3+ months): the first send is a re-permission or re-confirm, not a promo.
What ships with it
15 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.
- critique.md 32 KB
- references/benchmarks.md 1.9 KB
- references/copy-craft.md 3.5 KB
- references/deliverability.md 5.7 KB
- references/flow-library.md 14 KB
- references/intake.md 6.5 KB
- references/loadable-flow-format.md 8.2 KB
- references/modes-and-incidents.md 5.5 KB
- references/run-memory.md 8.9 KB
- references/segments-cadence-offers.md 5.1 KB
- references/sms-push-whatsapp.md 3.1 KB
- references/worked-flows.md 8.9 KB
- server-needs.md 4.6 KB
- skill.meta.json 5.5 KB
- tests/test-by-hand.md 9.1 KB
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.
- 4d ago First seen · 92 lines · 148 tokens per session scan A 15da64957bc9
email-lifecycle is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,265 stars, last pushed yesterday), licensed MIT. It adds 148 tokens to every session and 4,096 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-10-21.
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