Agent skill

disqualification-handling

Handles disqualified and near-miss inbound leads gracefully. Drafts polite rejection emails, referral requests (right company wrong person), and nurture routing (future fit). Ensures no inbound lead gets ignored and every disqualification preserves the relationship. Tool-agnostic.

gooseworks-aigithub.com/gooseworks-aiGitHub ↗
claude-codecodexcursorMIT
Install
npx skills add gooseworks-ai/goose-skills --skill disqualification-handling --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 15 KB
Bundled scripts: none
Version: 1.0.0
Path: skills/sales/composites/disqualification-handling/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,091
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Disqualification Handling Processes leads that didn't pass ICP qualification. Instead of ignoring them, this composite handles each category appropriately: polite rejection, referral request, or nurture routing. No inbound lead should feel ghosted. ## When to Auto-Load Load this composite when: - User says "handle the disqualified leads", "draft rejection emails", "what do we do with the ones that didn't qualify?" - `inbound-lead-qualification` has completed and disqualified/near-miss leads need handling - User has a list of leads that don't fit and wants appropriate responses ## Architecture ``` [Disqualified Leads] → Step 1: Categorize → Step 2: Draft Responses → Step 3: Route to Destination ↓ ↓ ↓ 4 handling categories Tailored email per type Nurture/CRM/archive ``` --- ## Step 0: Configuration (Once Per Client) On first run, establish response preferences. ```json { "sender_name": "", "sender_title": "", "company_name": "", "tone": "warm-professional | casual-friendly | formal", "nurture_sequence_tool": "Smartlead | HubSpot | Mailchimp | CSV export | none", "referral_incentive": "none | mention mutual value | offer resource", "include_resource_link": true, "resource_url": "",

What's inside
Steps it walks through
  1. When to Auto-Load
  2. Architecture
  3. Step 0: Configuration (Once Per Client)
  4. Step 1: Categorize Disqualified Leads
  5. Input
  6. Category 1: Right Company, Wrong Person → REFERRAL REQUEST
  7. Category 2: Close But Not Quite → NURTURE (FUTURE FIT)
  8. Category 3: Clearly Outside ICP → POLITE DECLINE
  9. Category 4: Special Flags → ROUTE DIFFERENTLY
  10. Output
  11. Step 2: Draft Responses
  12. Category 1 Response: Referral Request Email
  13. Category 2 Response: Nurture Warm-Down Email
  14. Category 3 Response: Polite Decline Email
Ships with 1 file
  • skill.meta.json
More from goose-skills
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About this skill
What does the disqualification-handling skill do?

Handles disqualified and near-miss inbound leads gracefully. Drafts polite rejection emails, referral requests (right company wrong person), and nurture routing (future fit). Ensures no inbound lead gets ignored and every disqualification preserves the relationship. Tool-agnostic.

How do I install it?

Run `npx skills add gooseworks-ai/goose-skills --skill disqualification-handling --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From gooseworks-ai/goose-skills, a repository with 1,091 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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