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 leadership-change-outreachgit 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/leadership-change-outreach)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/leadership-change-outreach"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/leadership-change-outreach/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/leadership-change-outreach"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/leadership-change-outreach.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 256 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00079 | $0.07522 |
| Opus 5 | $0.00039 | $0.03761 |
| Sonnet 5 | $0.00016 | $0.01504 |
| Haiku 4.5 | $0.00008 | $0.00752 |
Grade A, and why
leadership-change-outreach 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 — 722 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Leadership Change Outreach
Detects new leadership hires at target companies and evaluates whether the new leader is relevant to your product — as a direct buyer, a champion, or someone whose mandate aligns with what you sell. If relevant, enriches their profile and drafts personalized outreach that speaks to their new-role priorities.
Why leadership changes work: New leaders re-evaluate everything in their first 90 days. They inherit a vendor stack they didn't choose, a team they didn't build, and KPIs they need to hit fast. They're the most receptive buyers in any organization because:
- They want to put their stamp on the department
- They have a mandate (and often budget) to make changes
- They need quick wins to build credibility with their new org
- They haven't yet formed loyalty to existing vendors
When to Auto-Load
Load this composite when:
- User says "check for leadership changes", "new executive hires", "leadership signal outreach"
- User has a list of companies and wants to find those with relevant new leaders
- An upstream workflow (TAM Pulse, company monitoring) triggers a leadership change check
Detection Method: Apollo (Free Search + Enrichment)
This composite uses a two-phase Apollo pipeline that replaces slower web search approaches:
- Apollo Free Search —
search_peoplewithq_organization_domains+person_titlesfilters. Returns person IDs, obfuscated names, and titles. No credits consumed. Scans 100+ people across dozens of companies in ~30 seconds. - Local Post-Filter — Strict title matching to remove noise from Apollo's fuzzy matching (regional titles, sub-function heads, non-GTM roles). Typically reduces results by 50-60%.
- Apollo Enrichment by ID —
people/matchwith the personidfrom free search. Returns full employment history withstart_date/end_datefor every role, LinkedIn URL, verified email, and full name. Costs 1 credit per person. - Change Detection — Filter enriched results by
start_dateon thecurrent: trueemployment entry within the lookback window.
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 · 722 lines · 79 tokens per session scan A fd5c03706856
leadership-change-outreach is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 79 tokens to every session and 7,522 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.
Other skills, from other repositories
sequence-architect
Design a 4-6 touch outreach cadence with channels, timing, tonal arc, and branching. Use when starting a new sequence from scratch given an ICP and offer.
icebreaker
Draft 3 distinct opening messages for a specific prospect, anchored on a why-now and a why-this-person. Use when sending a high-leverage first touch where personalization is worth the time.
sequence-doctor
Audit an outreach sequence and produce a ranked fix list. Use when reply rates are low, when you want a second opinion before sending, or when rewriting a sequence from scratch.
jargon-bingo
Score sales calls, emails, or posts on a 5x5 bingo card of cliches. Mostly for fun; quietly useful for spotting jargon-heavy patterns.
prospect-twin
Build a believable persona simulation of a prospect from their LinkedIn profile, then practice outreach against them. Use when preparing for a high-stakes outreach or call, when iterating on openers, or when testing whether a pitch lands.
cringe-translator
Translate sales-jargon-laden LinkedIn messages into what the sender actually means. Mostly for fun; occasionally educational about why a message tanked.