Agent skill

Expansion Signal Spotter

by gooseworks-ai in gooseworks-ai/goose-skills

Monitor existing customer accounts for upsell and cross-sell signals: team growth on LinkedIn, new job postings, product usage patterns, funding announcements, and public company news.

MITAuto-check passedProductivity & Automation

Install Expansion Signal Spotter

skills CLI
$ npx skills add gooseworks-ai/goose-skills --skill expansion-signal-spotter -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install gooseworks-ai/goose-skills expansion-signal-spotter --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/sales/composites/expansion-signal-spotter .claude/skills/expansion-signal-spotter && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
expansion-signal-spotter
GitHub stars
1.2k
Used in
1 other repo
Token cost
~2.3k tokens
SKILL.md length
671 words
Files
2
Skills in repo
273
Repo updated
First seen
Licence
MIT

At a glance

Monitor existing customer accounts for upsell and cross-sell signals: team growth on LinkedIn, new job postings, product usage patterns, funding announcements, and public company news.

  • Works in 5 steps: Intake → Signal Detection → Opportunity Scoring → …
  • Tasks that involve Resume and CV writing
  • SKILL.md covers When to Use, Phase 0: Intake, Phase 1: Signal Detection and Phase 2: Opportunity Scoring, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Expansion Signal Spotter is an agent skill from gooseworks-ai/goose-skills. Monitor existing customer accounts for upsell and cross-sell signals: team growth on LinkedIn, new job postings, product usage patterns, funding announcements, and public company news. Produces a weekly expansion opportunity list with context and talk tracks. Chains web search, LinkedIn profile monitoring, and job posting detection.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill.meta.json`).

It sits in Productivity & Automation, covering Resume and CV writing and Web search. It works with LinkedIn. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.

When your agent uses it

  • Tasks that involve Resume and CV writing
  • Tasks that involve Web search

Example prompts

  • “/expansion-signal-spotter”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Intake
  2. Signal Detection
  3. Opportunity Scoring
  4. Talk Track Generation
  5. Output Format

What it can do on your machine

Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Expansion Signal Spotter loads about 2.3k tokens when it runs. Until then it costs about 90 tokens; SKILL.md has 671 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~90
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 671 words, ~2,300 tokens.

Download SKILL.mdSave it as .claude/skills/expansion-signal-spotter/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
expansion-signal-spotter
description
Monitor existing customer accounts for upsell and cross-sell signals: team growth on LinkedIn, new job postings, product usage patterns, funding announcements, and public company news. Produces a weekly expansion opportunity list with context and talk tracks. Chains web search, LinkedIn profile monitoring, and job posting detection.
tags
lead-generation

Expansion Signal Spotter

Find expansion revenue hiding in your existing customer base. Monitors accounts for signals that indicate they're ready to buy more — before they ask or before a competitor gets there first.

Built for: CS teams and founders at early-stage companies where expansion revenue is the fastest path to growth. You already have the relationship — this skill finds the timing.

When to Use

  • "Which customers are ready to expand?"
  • "Find upsell opportunities in our accounts"
  • "Run the weekly expansion signal scan"
  • "Who should I pitch [new feature/tier] to?"
  • "Monitor customer accounts for growth signals"

Phase 0: Intake

Account Data
  1. Customer list — CSV or sheet with: company name, domain, primary contact LinkedIn URL, current plan/tier, MRR/ARR, seats/usage
  2. Product tiers — What plans exist? What triggers an upgrade? (e.g., "Pro → Enterprise at 50+ seats")
  3. Cross-sell products — Any add-ons or adjacent products you can sell?
Signal Configuration
  1. Expansion triggers — What signals mean "ready to buy more" for your product?
    • Team growth (new hires in relevant roles)
    • Funding announcement
    • Usage hitting plan limits
    • New department/use case interest
    • Champion promoted (more budget authority)
  2. Key contacts to monitor — LinkedIn URLs of champions, decision-makers per account (if available beyond primary)
Filters
  1. Minimum account value — Only scan accounts above $X MRR? (Focus effort)
  2. Accounts to exclude — Any accounts in active churn risk, paused, or in dispute

Phase 1: Signal Detection

1A: Team Growth Signals

For each customer, search for hiring activity:

Search: "[company name]" hiring OR "we're hiring" OR "join our team"
Search: site:linkedin.com/jobs "[company name]" [relevant role keywords]
Search: "[company name]" "head of" OR "director of" OR "VP" [your product's domain]

Signals to detect:

SignalWhat It MeansExpansion Play
Hiring in your product's domainGrowing the team that uses youMore seats / higher tier
New leadership hireBudget holder arrived, will evaluate stackExecutive alignment meeting
Hiring in adjacent teamNew department could use your productCross-sell / new use case
Rapid headcount growthScaling fast, needs to scale tools tooVolume upgrade
1B: Funding & Financial Signals
Search: "[company name]" funding OR raised OR "series" OR investment 2026
Search: "[company name]" revenue OR growth OR expansion
SignalWhat It MeansExpansion Play
New funding roundCash in bank, expanding everythingPremium tier / annual contract
Revenue milestoneBusiness doing well, likely investing in toolsROI-focused expansion pitch
AcquisitionNew parent company = new budgetEnterprise plan / multi-team
1C: Product Usage Signals (if usage data available)

From internal data, flag:

SignalThresholdExpansion Play
Approaching plan limit>80% of seats/usage quotaProactive upgrade offer
New feature adoptionStarted using a feature in higher tier (via trial/beta)Convert trial to paid
Power user emergence1+ users with 3x average usageChampion for internal expansion
Multi-team usageUsers from 2+ departmentsDepartment-level deal
API usage growthAPI calls trending up month-over-monthUsage-based tier upgrade
Show full SKILL.md (252 more words)Show less
1D: Public Signal Monitoring
Search: "[company name]" launch OR "new product" OR partnership OR expansion
Search: "[company name]" "[your product category]" OR "[related use case]"
SignalWhat It MeansExpansion Play
New product launchMay need your product for the new lineNew use case pitch
Geographic expansionGrowing into new marketsMulti-region / additional seats
Partnership announcedBusiness growing, more complexityHigher tier for scale
Competitor of yours mentionedEvaluating alternativesRetention + upgrade pre-empt
1E: Champion & Stakeholder Signals

If monitoring champion LinkedIn profiles:

Search: "[champion name]" promoted OR "new role" OR "excited to announce"
SignalWhat It MeansExpansion Play
Champion promotedMore authority, bigger budgetPropose expansion aligned to new scope
Champion leftRisk + opportunity (new person = fresh pitch)Onboard new contact, re-pitch value
New exec joinedPotential new sponsorExecutive briefing

Phase 2: Opportunity Scoring

Score each expansion opportunity:

Expansion Score = Signal Strength × Account Value × Timing

Signal Strength (1-5):
  5 = Approaching plan limit + funding + team growth (multiple signals)
  4 = Strong usage signal + one external signal
  3 = One strong external signal (funding, hiring)
  2 = Usage trending up, no external confirmation
  1 = Weak or single minor signal

Account Value (multiplier):
  2.0x = Top 20% accounts by MRR
  1.5x = Mid-tier accounts
  1.0x = Smaller accounts

Timing (multiplier):
  2.0x = Signal detected this week (fresh)
  1.5x = Signal detected this month
  1.0x = Signal older than 30 days
Opportunity Tiers
TierScoreAction
Hot15+Schedule expansion call this week
Warm8-14Send value-add touchpoint, plant expansion seed
Watch3-7Add to next QBR agenda, monitor

Phase 3: Talk Track Generation

For each Hot and Warm opportunity, generate:

ACCOUNT: [Company Name]
CURRENT PLAN: [Plan] — $[MRR]/mo
EXPANSION TYPE: [Upsell / Cross-sell / Volume increase]
ESTIMATED EXPANSION: $[additional MRR]/mo

SIGNALS:
- [Signal 1] — [Source + date]
- [Signal 2] — [Source + date]

EXPANSION OPPORTUNITY:
[2-3 sentences: What should they buy and why now?]

TALK TRACK:
"[Opening line — connects the signal to their business goals, not your quota]"

"[Value bridge — how the expansion directly helps with what they're already trying to do]"

"[Soft ask — suggest next step without pressure]"

TIMING: [Why now is the right time — tied to signal]

RISK: [What could block this — budget freeze, champion change, etc.]

Phase 4: Output Format

markdown
# Expansion Signal Report — Week of [DATE]
Accounts scanned: [N]
Total expansion pipeline identified: $[X] additional MRR

---

## Summary

| Tier | Opportunities | Potential MRR |
|------|--------------|---------------|
| 🔥 Hot | [N] | $[X]/mo |
| 🟡 Warm | [N] | $[X]/mo |
| 👀 Watch | [N] | $[X]/mo |

---

## 🔥 Hot Opportunities

### [Company 1] — Current: $[X]/mo → Target: $[Y]/mo (+$[Z])
**Signals:** [list]
**Expansion type:** [Upsell to Enterprise / Add 20 seats / Cross-sell analytics]
**Talk track:** "[scripted opener]"
**Next step:** [Specific action + date]

### [Company 2] — ...

---

## 🟡 Warm Opportunities

### [Company] — Current: $[X]/mo | Signal: [brief]
**Recommended touchpoint:** [What to do — e.g., "Send case study of similar customer who expanded"]

---

## 👀 Watch List

| Account | Signal | Next Check |
|---------|--------|------------|
| [Name] | [Signal] | [Date] |

---

## Trends

- [N] accounts showing team growth signals (potential seat expansion)
- [N] accounts approaching usage limits
- [N] accounts with new funding (potential tier upgrade)

## Expansion Playbook Priority

This week, focus on:
1. **[Account]** — [Why: highest value + strongest signal]
2. **[Account]** — [Why]
3. **[Account]** — [Why]

Save to the current working directory or wherever the user prefers (e.g., expansion/expansion-signals-[YYYY-MM-DD].md).

Scheduling

Run weekly:

bash
0 8 * * 2 python3 run_skill.py expansion-signal-spotter

Cost

ComponentCost
Web search (hiring, funding, news)Free
LinkedIn monitoring (if using linkedin-profile-post-scraper)~$0.50-1.00
Job posting detection (if using job-posting-intent)~$0.50
All analysis and talk tracksFree (LLM reasoning)
TotalFree — $1.50

Tools Required

  • web_search — for funding, news, hiring signals
  • fetch_webpage — for career pages and announcements
  • Optional: linkedin-profile-post-scraper for champion monitoring
  • Optional: job-posting-intent for structured hiring signal detection

Trigger Phrases

  • "Find expansion opportunities in our accounts"
  • "Which customers are ready for an upgrade?"
  • "Run the expansion signal scan"
  • "Weekly expansion opportunity report"

© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/sales/composites/expansion-signal-spotter of gooseworks-ai/goose-skills.

  • SKILL.md
  • skill.meta.json

Open the folder on GitHubat commit c650c6d

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in gooseworks-ai/goose-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Expansion Signal Spotter next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Expansion Signal Spotter this skillgooseworks-ai/goose-skills1.2k1 repos~2.3kAutomated safety check: PassMIT
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Agent ReachEdisonChenAI/agent-reach1151 repos~1.3kAutomated safety check: PassMIT
Bright Data MCPbrightdata/skills2641 repos~3.7kAutomated safety check: PassMIT
Company Researchliangdabiao/exa-research-mcp-skill110—~1.1kAutomated safety check: PassNone

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Works with

Questions about Expansion Signal Spotter

What does Expansion Signal Spotter do?

Monitor existing customer accounts for upsell and cross-sell signals: team growth on LinkedIn, new job postings, product usage patterns, funding announcements, and public company news. Expansion Signal Spotter is an agent skill from gooseworks-ai/goose-skills. Monitor existing customer accounts for upsell and cross-sell signals: team growth on LinkedIn, new job postings, product usage patterns, funding announcements, and public company news.

When should I use Expansion Signal Spotter?

Expansion Signal Spotter fits situations like: tasks that involve Resume and CV writing; tasks that involve Web search.

How do I install Expansion Signal Spotter in Claude Code?

Run `npx skills add gooseworks-ai/goose-skills --skill expansion-signal-spotter -a claude-code`. Or copy the skill folder (skills/sales/composites/expansion-signal-spotter in gooseworks-ai/goose-skills) into .claude/skills/expansion-signal-spotter in your project. Claude Code loads it when a task matches its description.

How do I install Expansion Signal Spotter in Codex?

Run `npx skills add gooseworks-ai/goose-skills --skill expansion-signal-spotter -a codex`. Or copy the skill folder (skills/sales/composites/expansion-signal-spotter in gooseworks-ai/goose-skills) into .agents/skills/expansion-signal-spotter in your project. Codex loads it when a task matches its description.

Can I use Expansion Signal Spotter in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill expansion-signal-spotter -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/expansion-signal-spotter, .gemini/skills/expansion-signal-spotter, .github/skills/expansion-signal-spotter and .opencode/skills/expansion-signal-spotter in your project.

What does Expansion Signal Spotter need to run?

SKILL.md names no scripts, command-line tools or credentials: Expansion Signal Spotter is instructions for the agent only. Our summary lists: Python 3.

Does Expansion Signal Spotter access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Expansion Signal Spotter safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Expansion Signal Spotter use?

Expansion Signal Spotter is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Expansion Signal Spotter use?

About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Expansion Signal Spotter?

Skills that share tags, products or a category with Expansion Signal Spotter: Curviate Profile (davila7/claude-code-templates, 33k stars), Agent Reach (Panniantong/Agent-Reach, 95k stars), Agent Reach (EdisonChenAI/agent-reach, 115 stars) and Bright Data MCP (brightdata/skills, 264 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Expansion Signal Spotter?

gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.

Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.