domain-expired-opportunity-finder

Name: domain-expired-opportunity-finder
Author: Varnan-Tech

20installs59forks

How to install domain-expired-opportunity-finder?

varnan-tech/opendirectory/domain-expired-opportunity-finder

$npx -y skills add Varnan-Tech/opendirectory --skill domain-expired-opportunity-finder

Installs into the current project.

Summary

Evaluates expired domain candidates against a target niche, scores them by topical relevance, historical activity level, and history cleanliness, then outputs a ranked shortlist with explainable reasoning and risk flags.

Files · 1

View on GitHub

SKILL.md

1	# Expired Domain Opportunity Finder
2
3	Evaluate expired domain candidates for a specific niche. Score them on topical
4	fit, historical activity level, history cleanliness, and redirect suitability. Output a
5	conservative, explainable shortlist for human review.
6
7	---
8
9	Critical rule: Every recommendation must include BOTH a positive rationale
10	(`why_selected`) AND a caution rationale (`why_risky`). Never output a bare
11	score without explanation.
12
13	Conservative-by-default rule: When signals are incomplete or contradictory,
14	lower the confidence level. Do not surface ambiguous candidates as strong
15	opportunities. Missing data reduces confidence, never inflates it.
16
17	Anti-abuse rule: Never encourage unrelated redirects, PBN construction, or
18	domain repurposing where the historical topic does not match the target niche.
19	Read `references/guardrails.md` for the full anti-abuse policy.
20
21	---
22
23	## Step 1: Setup Check
24
25	Check the environment before doing anything else.
26
27	Verify that `curl` and `python3` (or `python`) are available:
28	```bash
29	curl --version > /dev/null 2>&1 && echo "curl: available" \|\| echo "curl: MISSING"
30	python3 --version 2>/dev/null \|\| python --version 2>/dev/null \|\| echo "python: MISSING"
31	```
32
33	Check for an optional LLM API key for enhanced niche-relevance scoring:
34	```bash
35	echo "LLM_API_KEY: ${LLM_API_KEY:+set}"
36	```
37
38	If `curl` or `python` is missing:
39	Stop. Tell the user: "This skill requires curl and Python 3.10+. Please install them and try again."
40
41	If `LLM_API_KEY` is not set:
42	Continue. The skill will use rule-based scoring only (domain string matching,
43	Wayback title analysis, keyword overlap). Note to the user: "Running in
44	rule-based-only mode. Set LLM_API_KEY for enhanced niche-relevance scoring."
45
46	If `LLM_API_KEY` is set:
47	The skill will use LLM-enhanced scoring for topical relevance analysis.
48	This provides deeper contextual assessment of niche fit.
49
50	QA: State the scoring mode (llm-enhanced or rule-based-only) and confirm tools are available.
51
52	---
53
54	## Step 2: Input Collection
55
56	Collect the required and optional inputs from the user.
57
58	Required:
59	- `target_niche` (string): The core niche to evaluate against. Examples: "developer tools", "AI SaaS", "cybersecurity", "fintech".
60
61	Optional (ask only if not provided):
62	- `seed_keywords` (array): Keywords to refine topical matching. If not provided, extract 3–5 keywords from the niche name automatically.
63	- `candidate_domains` (array): Specific domains to evaluate. If not provided, prompt the user.
64	- `discovery_source` (string): Where candidates came from — `manual`, `expireddomains-net`, `external-feed`.
65	- `min_snapshots` (integer): Minimum historical snapshot threshold. Default: 10.
66	- `max_risk_level` (string): `low`, `medium`, or `high`. Controls how aggressively risky candidates are filtered. Default: `medium`.
67	- `intended_use` (string): `rebuild`, `redirect`, or `either`. Default: `either`.
68
69	If no `candidate_domains` are provided:
70	Ask: "Please provide a list of expired domain candidates to evaluate. You can:
71	1. Paste domain names (one per line or comma-separated)
72	2. Provide a file path to a text file with one domain per line
73	3. Say 'example' to run with a built-in demo set for the 'developer tools' niche"
74
75	If the user says 'example':
76	Use this demo set:
77	```
78	devtoolsweekly.com
79	codeshipnews.io
80	stackforgeapp.com
81	quickseorank.net
82	bestcheaphosting247.com
83	cloudbuildpro.dev
84	reactwidgetlib.com
85	megadealsshop.xyz
86	```
87
88	After collecting all inputs, confirm:
89	"Target niche: [niche]. Evaluating [N] candidate domains. Scoring mode: [mode]. Intended use: [use]."
90
91	---
92
93	## Step 3: Candidate Normalization
94
95	Clean and validate the candidate list before scoring.
96
97	```bash
98	python3 -c "
99	import sys, re
100
101	domains = '''CANDIDATE_LIST_HERE'''.strip().split('\n')
102	seen = set()
103	valid = []
104	invalid = []
105
106	for d in domains:
107	d = d.strip().lower()
108	# Strip protocols and paths
109	d = re.sub(r'^https?://', '', d)
110	d = d.split('/')[0]
111	d = d.strip('.')
112
113	if not d:
114	continue
115
116	# Basic TLD validation
117	if '.' not in d or len(d) < 4:
118	invalid.append(d)
119	continue
120
121	# Deduplicate
122	if d in seen:
123	continue
124	seen.add(d)
125	valid.append(d)
126
127	print(f'Valid candidates: {len(valid)}')
128	print(f'Removed (invalid/duplicate): {len(invalid)}')
129	for v in valid:
130	print(f' ✓ {v}')
131	for i in invalid:
132	print(f' ✗ {i} (invalid format)')
133	"
134	```
135
136	Replace `CANDIDATE_LIST_HERE` with the actual domain list from Step 2.
137
138	State: "[N] valid candidates after normalization. [M] removed (invalid/duplicate)."
139
140	If 0 valid candidates remain, stop and tell the user: "No valid

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domain-expired-opportunity-finder

20installs59forks

View on GitHub

How to install domain-expired-opportunity-finder?

varnan-tech/opendirectory/domain-expired-opportunity-finder

$npx -y skills add Varnan-Tech/opendirectory --skill domain-expired-opportunity-finder

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Expired Domain Opportunity Finder
2
3	Evaluate expired domain candidates for a specific niche. Score them on topical
4	fit, historical activity level, history cleanliness, and redirect suitability. Output a
5	conservative, explainable shortlist for human review.
6
7	---
8
9	Critical rule: Every recommendation must include BOTH a positive rationale
10	(`why_selected`) AND a caution rationale (`why_risky`). Never output a bare
11	score without explanation.
12
13	Conservative-by-default rule: When signals are incomplete or contradictory,
14	lower the confidence level. Do not surface ambiguous candidates as strong
15	opportunities. Missing data reduces confidence, never inflates it.
16
17	Anti-abuse rule: Never encourage unrelated redirects, PBN construction, or
18	domain repurposing where the historical topic does not match the target niche.
19	Read `references/guardrails.md` for the full anti-abuse policy.
20
21	---
22
23	## Step 1: Setup Check
24
25	Check the environment before doing anything else.
26
27	Verify that `curl` and `python3` (or `python`) are available:
28	```bash
29	curl --version > /dev/null 2>&1 && echo "curl: available" \|\| echo "curl: MISSING"
30	python3 --version 2>/dev/null \|\| python --version 2>/dev/null \|\| echo "python: MISSING"
31	```
32
33	Check for an optional LLM API key for enhanced niche-relevance scoring:
34	```bash
35	echo "LLM_API_KEY: ${LLM_API_KEY:+set}"
36	```
37
38	If `curl` or `python` is missing:
39	Stop. Tell the user: "This skill requires curl and Python 3.10+. Please install them and try again."
40
41	If `LLM_API_KEY` is not set:
42	Continue. The skill will use rule-based scoring only (domain string matching,
43	Wayback title analysis, keyword overlap). Note to the user: "Running in
44	rule-based-only mode. Set LLM_API_KEY for enhanced niche-relevance scoring."
45
46	If `LLM_API_KEY` is set:
47	The skill will use LLM-enhanced scoring for topical relevance analysis.
48	This provides deeper contextual assessment of niche fit.
49
50	QA: State the scoring mode (llm-enhanced or rule-based-only) and confirm tools are available.
51
52	---
53
54	## Step 2: Input Collection
55
56	Collect the required and optional inputs from the user.
57
58	Required:
59	- `target_niche` (string): The core niche to evaluate against. Examples: "developer tools", "AI SaaS", "cybersecurity", "fintech".
60
61	Optional (ask only if not provided):
62	- `seed_keywords` (array): Keywords to refine topical matching. If not provided, extract 3–5 keywords from the niche name automatically.
63	- `candidate_domains` (array): Specific domains to evaluate. If not provided, prompt the user.
64	- `discovery_source` (string): Where candidates came from — `manual`, `expireddomains-net`, `external-feed`.
65	- `min_snapshots` (integer): Minimum historical snapshot threshold. Default: 10.
66	- `max_risk_level` (string): `low`, `medium`, or `high`. Controls how aggressively risky candidates are filtered. Default: `medium`.
67	- `intended_use` (string): `rebuild`, `redirect`, or `either`. Default: `either`.
68
69	If no `candidate_domains` are provided:
70	Ask: "Please provide a list of expired domain candidates to evaluate. You can:
71	1. Paste domain names (one per line or comma-separated)
72	2. Provide a file path to a text file with one domain per line
73	3. Say 'example' to run with a built-in demo set for the 'developer tools' niche"
74
75	If the user says 'example':
76	Use this demo set:
77	```
78	devtoolsweekly.com
79	codeshipnews.io
80	stackforgeapp.com
81	quickseorank.net
82	bestcheaphosting247.com
83	cloudbuildpro.dev
84	reactwidgetlib.com
85	megadealsshop.xyz
86	```
87
88	After collecting all inputs, confirm:
89	"Target niche: [niche]. Evaluating [N] candidate domains. Scoring mode: [mode]. Intended use: [use]."
90
91	---
92
93	## Step 3: Candidate Normalization
94
95	Clean and validate the candidate list before scoring.
96
97	```bash
98	python3 -c "
99	import sys, re
100
101	domains = '''CANDIDATE_LIST_HERE'''.strip().split('\n')
102	seen = set()
103	valid = []
104	invalid = []
105
106	for d in domains:
107	d = d.strip().lower()
108	# Strip protocols and paths
109	d = re.sub(r'^https?://', '', d)
110	d = d.split('/')[0]
111	d = d.strip('.')
112
113	if not d:
114	continue
115
116	# Basic TLD validation
117	if '.' not in d or len(d) < 4:
118	invalid.append(d)
119	continue
120
121	# Deduplicate
122	if d in seen:
123	continue
124	seen.add(d)
125	valid.append(d)
126
127	print(f'Valid candidates: {len(valid)}')
128	print(f'Removed (invalid/duplicate): {len(invalid)}')
129	for v in valid:
130	print(f' ✓ {v}')
131	for i in invalid:
132	print(f' ✗ {i} (invalid format)')
133	"
134	```
135
136	Replace `CANDIDATE_LIST_HERE` with the actual domain list from Step 2.
137
138	State: "[N] valid candidates after normalization. [M] removed (invalid/duplicate)."
139
140	If 0 valid candidates remain, stop and tell the user: "No valid

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6 picks

Type