deep-research

Name: deep-research
Author: jezweb

951installs96forks

How to install deep-research?

jezweb/claude-skills/deep-research

$npx -y skills add jezweb/claude-skills --skill deep-research

Installs into the current project.

Summary

Deep research and discovery before building something new. Explores local projects for reusable code, researches competitors, reads forums and reviews, analyses plugin ecosystems, investigates technical options, and produces a comprehensive research brief. Three depths: focused (

Files · 1

View on GitHub

SKILL.md

1	# Deep Research
2
3	Comprehensive research and discovery before building something new. Instead of jumping straight into code from training data, this skill goes wide and deep — local exploration, web research, competitor analysis, ecosystem signals, future-casting — and produces a research brief that makes the actual build 10x more productive.
4
5	## Depth Levels
6
7	The difference is scope of ambition, not just time.
8
9	\| Depth \| Purpose \| Scope \|
10	\|-------\|---------\|-------\|
11	\| focused \| Answer a specific question \| One decision: "CodeMirror vs ProseMirror?" — targeted search, local scan, 1-2 comparisons. Produces a 1-page recommendation. \|
12	\| wide \| Understand the space \| Landscape for a new product or feature. Competitors, ecosystem, user needs, architecture options. Enough to write a spec. \|
13	\| deep \| Plan a major build \| Leave no stone unturned. Everything in wide PLUS library/component research, plugin ecosystems, GitHub issues mining, community sentiment, future-casting, technical deep-dives on every decision. Enough to drive weeks of coding. \|
14
15	Default: wide
16
17	## Workflow
18
19	### 1. Understand the Intent
20
21	Ask the user:
22	- What are you building? (one sentence)
23	- Why? What problem does it solve? Who's it for?
24	- Constraints? Stack preferences, budget, timeline, must-haves?
25	- Existing work? Any projects to build on? Repos to look at?
26
27	If the user gives a brief prompt ("obsidian replacement on cloudflare"), that's enough — fill in the gaps through research.
28
29	### 2. Local Exploration
30
31	Scan the user's machine for relevant prior work:
32
33	```bash
34	# Find related projects by name/keyword
35	ls ~/Documents/ \| grep -i "KEYWORD"
36
37	# Read CLAUDE.md of related projects for architecture context
38	find ~/Documents -maxdepth 2 -name "CLAUDE.md" -exec grep -l "KEYWORD" {} \;
39
40	# Check for reusable patterns, schemas, components
41	find ~/Documents -maxdepth 3 -name "schema.ts" -o -name "ARCHITECTURE.md" \| head -20
42	```
43
44	For each related project found:
45	- Read CLAUDE.md (stack, architecture, gotchas)
46	- Check for reusable code (schemas, components, utilities, configs)
47	- Note what worked well and what didn't (from git history, TODO comments)
48
49	Also check:
50	- Basalt Cortex (`~/Documents/basalt-cortex/`) for related clients, contacts, knowledge facts
51	- `grep -rl "KEYWORD" ~/Documents/basalt-cortex/ --include="*.md"`
52
53	### 3. Web Research
54
55	Search broadly to understand the space:
56
57	- Product category: "markdown note app", "knowledge management tool for teams"
58	- Competitors: find top 5-10 by searching "best X", "X alternatives", "X vs Y"
59	- Open source: search GitHub for open-source alternatives, check star counts
60	- Architecture: "how to build X", "X tech stack", "building X with [framework]"
61	- Technology docs: check llms.txt, official docs for key technologies
62	- Platform examples: "built with Cloudflare Workers", "D1 full-text search example"
63	- Tutorials and case studies: "building a Y from scratch", "lessons learned building Z"
64
65	### 4. Ecosystem and Community Research (wide + deep)
66
67	Go beyond the core product — the ecosystem reveals what users actually need:
68
69	Plugins and add-ons:
70	- What plugins exist for major competitors? The most popular ones reveal what the core product lacks.
71	- e.g. Obsidian has 1800+ plugins — the top 20 tell you what Obsidian doesn't do well natively.
72	- Search: "top [product] plugins", "[product] plugin directory"
73
74	GitHub issues and feature requests:
75	- Check top competitors' GitHub repos for most-upvoted issues
76	- Sort by thumbs-up reactions — this is direct user demand signal
77	- Check closed issues for how features were implemented
78
79	Forum discussions:
80	- Reddit: r/[product], r/selfhosted, r/webdev, relevant niche subreddits
81	- Hacker News: search for the product category
82	- Discord/Discourse: product-specific communities
83	- What do users love? What do they complain about? What do they wish existed?
84
85	App store and review sites:
86	- 1-star reviews = unmet needs (the product fails at this)
87	- 5-star reviews = what to preserve (users love this, don't break it)
88	- 3-star reviews = the interesting middle (it's okay but...)
89	- Search: ProductHunt, G2, Capterra, App Store reviews
90
91	Integration requests:
92	- What systems do users want to connect to? (Zapier integrations, API requests)
93	- These reveal real workflows

People who liked this also viewed

6 picks

Type

deep-research

951installs96forks

View on GitHub

How to install deep-research?

jezweb/claude-skills/deep-research

$npx -y skills add jezweb/claude-skills --skill deep-research

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Deep Research
2
3	Comprehensive research and discovery before building something new. Instead of jumping straight into code from training data, this skill goes wide and deep — local exploration, web research, competitor analysis, ecosystem signals, future-casting — and produces a research brief that makes the actual build 10x more productive.
4
5	## Depth Levels
6
7	The difference is scope of ambition, not just time.
8
9	\| Depth \| Purpose \| Scope \|
10	\|-------\|---------\|-------\|
11	\| focused \| Answer a specific question \| One decision: "CodeMirror vs ProseMirror?" — targeted search, local scan, 1-2 comparisons. Produces a 1-page recommendation. \|
12	\| wide \| Understand the space \| Landscape for a new product or feature. Competitors, ecosystem, user needs, architecture options. Enough to write a spec. \|
13	\| deep \| Plan a major build \| Leave no stone unturned. Everything in wide PLUS library/component research, plugin ecosystems, GitHub issues mining, community sentiment, future-casting, technical deep-dives on every decision. Enough to drive weeks of coding. \|
14
15	Default: wide
16
17	## Workflow
18
19	### 1. Understand the Intent
20
21	Ask the user:
22	- What are you building? (one sentence)
23	- Why? What problem does it solve? Who's it for?
24	- Constraints? Stack preferences, budget, timeline, must-haves?
25	- Existing work? Any projects to build on? Repos to look at?
26
27	If the user gives a brief prompt ("obsidian replacement on cloudflare"), that's enough — fill in the gaps through research.
28
29	### 2. Local Exploration
30
31	Scan the user's machine for relevant prior work:
32
33	```bash
34	# Find related projects by name/keyword
35	ls ~/Documents/ \| grep -i "KEYWORD"
36
37	# Read CLAUDE.md of related projects for architecture context
38	find ~/Documents -maxdepth 2 -name "CLAUDE.md" -exec grep -l "KEYWORD" {} \;
39
40	# Check for reusable patterns, schemas, components
41	find ~/Documents -maxdepth 3 -name "schema.ts" -o -name "ARCHITECTURE.md" \| head -20
42	```
43
44	For each related project found:
45	- Read CLAUDE.md (stack, architecture, gotchas)
46	- Check for reusable code (schemas, components, utilities, configs)
47	- Note what worked well and what didn't (from git history, TODO comments)
48
49	Also check:
50	- Basalt Cortex (`~/Documents/basalt-cortex/`) for related clients, contacts, knowledge facts
51	- `grep -rl "KEYWORD" ~/Documents/basalt-cortex/ --include="*.md"`
52
53	### 3. Web Research
54
55	Search broadly to understand the space:
56
57	- Product category: "markdown note app", "knowledge management tool for teams"
58	- Competitors: find top 5-10 by searching "best X", "X alternatives", "X vs Y"
59	- Open source: search GitHub for open-source alternatives, check star counts
60	- Architecture: "how to build X", "X tech stack", "building X with [framework]"
61	- Technology docs: check llms.txt, official docs for key technologies
62	- Platform examples: "built with Cloudflare Workers", "D1 full-text search example"
63	- Tutorials and case studies: "building a Y from scratch", "lessons learned building Z"
64
65	### 4. Ecosystem and Community Research (wide + deep)
66
67	Go beyond the core product — the ecosystem reveals what users actually need:
68
69	Plugins and add-ons:
70	- What plugins exist for major competitors? The most popular ones reveal what the core product lacks.
71	- e.g. Obsidian has 1800+ plugins — the top 20 tell you what Obsidian doesn't do well natively.
72	- Search: "top [product] plugins", "[product] plugin directory"
73
74	GitHub issues and feature requests:
75	- Check top competitors' GitHub repos for most-upvoted issues
76	- Sort by thumbs-up reactions — this is direct user demand signal
77	- Check closed issues for how features were implemented
78
79	Forum discussions:
80	- Reddit: r/[product], r/selfhosted, r/webdev, relevant niche subreddits
81	- Hacker News: search for the product category
82	- Discord/Discourse: product-specific communities
83	- What do users love? What do they complain about? What do they wish existed?
84
85	App store and review sites:
86	- 1-star reviews = unmet needs (the product fails at this)
87	- 5-star reviews = what to preserve (users love this, don't break it)
88	- 3-star reviews = the interesting middle (it's okay but...)
89	- Search: ProductHunt, G2, Capterra, App Store reviews
90
91	Integration requests:
92	- What systems do users want to connect to? (Zapier integrations, API requests)
93	- These reveal real workflows

People who liked this also viewed

6 picks

Type