research
Skill501 starsChanged 7 months agoMITView on GitHub
Research a company before applying or interviewing. Get an intelligence brief with culture, financials, recent news, team structure, key contacts, and smart interview questions. Use when someone says 'research this company', 'tell me about', 'what do you know about', or 'prep me for my interview at'.
189 other projects use a version of this.
Adopted by
Most recently taken up by
- dialog-db/dialog-dbtheir own version, first seen Nov 9, 2026
- howells/skillstheir own version, first seen Nov 8, 2026
- xiaoxiaosrm/dsh-mattpocock-skillstheir own version, first seen Nov 8, 2026
- Suge8/friedbuntheir own version, first seen Nov 8, 2026
- wowyuarm/dsh-agent-teamtheir own version, first seen Nov 8, 2026
- Contexera/dsh-agent-teamtheir own version, first seen Nov 8, 2026
Used with
Projects with it also use daily-arxiv, exp-eval and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
LambenthanSkilldaily-arxiv
每日从 arXiv 拉取新论文,过滤相关性,auto-ingest 高优先级论文,检测 SOTA 更新
Also in 5 projects that use this
LambenthanSkillexp-eval
实验判决门:Review LLM 独立评判实验结果 → 4 种判决路径 → 自动更新 claims confidence、ideas status、graph edges
Also in 5 projects that use this
truongtv22SkillProblem-Solving Techniques
Apply systematic problem-solving techniques for complexity spirals (simplification cascades), innovation blocks (collision-zone thinking), recurring patterns (meta-pattern recognition), assumption constraints (inversion exercise), scale uncertainty (scale game), and dispatch when stuck. Techniques derived from Microsoft Amplifier project patterns adapted for immediate application.
Also in 5 projects that use this
liufeng1976Skillsetup-ts-deep-modules
Wire dependency-cruiser into a TypeScript repo so each package is a deep module — implementation hidden in subfolders, reachable only through its entry-point files. User-invoked.
Also in 43 projects that use this
skyllwtSkillexp-pilot-eval
Pilot result evaluation — read pilot results, apply success criteria, update idea page (pilot_result, failure_reason if failed), generate PILOT_VERDICT_REPORT. Called by /ideate Phase 5 after /exp-pilot-run.
Also in 4 projects that use this
skyllwtSkillexp-pilot-run
Pilot experiment execution — read Pilot Spec YAML, write pilot code, run experiment(Confirm with the user before operation and require the applicant to conduct manual inspection), return results. Called by /ideate Phase 5. Does NOT modify wiki pages or judge pass/fail.
Also in 4 projects that use this
- +5 more from Lambenthan
- +1 more from skyllwt
Other versions189 projects use a version of this.
Word for word · 1
Edited · 0
None found.
Wrote their own version · 188
- mattpocock/skills★ 309ksame name
- Yeachan-Heo/oh-my-claude-sisyphus★ 41ksame name
- Yeachan-Heo/oh-my-claudecode★ 41ksame name
- QuivrHQ/quivr★ 40ksame name
- The-Vibe-Company/quivr★ 40ksame name
- udecode/plate★ 17ksame name
- openai/plugins★ 7.8ksame name
- ArcReel/ArcReel★ 6.3ksame name
- vinvcn/mattpocock-skills-zh-CN★ 5.5ksame name
- withcoral/coral★ 4.9ksame name
178 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 3 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 168 edited versions we read keep these.
3
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 20
Use WebSearch to find:
- Distinctive: line 32
If WebSearch is unavailable:
- Distinctive: line 41
Search for likely hiring contacts:
- Very specific: line 53
Read data/evaluations/ for any evaluation at this company.
“Common” is measured: kept by at least 6 in 10 of the 168 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Company Research
Build an intelligence brief on a target company.
Step 1: Gather Data
Use WebSearch to find:
- Company basics: What they do, size, founded, HQ, funding/revenue
- Recent news (last 6 months): Product launches, layoffs, acquisitions, leadership changes, funding rounds
- Culture signals: Glassdoor rating + recurring themes, any "best places to work" lists or notable controversies
- Team/department: Who leads the department you'd join? Likely hiring manager? Team size?
- Tech/tools/methodology: What does this team use? (Check job postings, tech blog, team member LinkedIn profiles via web search)
If WebSearch is unavailable:
"I can share what I know about {company}, but for the latest info (recent news, Glassdoor reviews, team changes), enable web search in your settings. Here's what I can tell you from general knowledge:"
Then provide what you know, clearly labeled as potentially outdated.
Step 2: Find Contacts
Search for likely hiring contacts:
- Hiring manager (head of the relevant department)
- Recruiter (search "{company} recruiter {department}")
- Team members (potential peers for informational outreach)
For each contact found: Name, Title, and where you found them.
Note: Do NOT scrape LinkedIn profiles directly. Use web search results and public company pages only.
Step 3: Check for Existing Evaluation
Read data/evaluations/ for any evaluation at this company. If found,
reference it to add context to the brief.
Step 4: Output
## Company Brief: {Company Name}
### Overview
| Field | Detail |
|---|---|
| **Industry** | {industry} |
| **Size** | {employee count range} |
| **Founded** | {year} |
| **HQ** | {location} |
| **Revenue/Funding** | {if available} |
| **Website** | {URL} |
### Recent News (Last 6 Months)
- {headline} ({source}, {date})
- ...
(If no news found: "No major recent news found.")
### Culture Snapshot
**Glassdoor:** {rating}/5 ({review count} reviews)
**Positive themes:** {what employees like}
**Negative themes:** {common complaints}
**Work style:** {remote/hybrid/in-office, hours culture}
### Key Contacts
| Name | Title | Source |
|---|---|---|
| {name} | {title} | {where found} |
### Interview Intelligence
- **Company values/mission:** {what they emphasize}
- **Current priorities:** {what they're working on now}
- **Smart questions to ask:**
1. {question based on recent news or strategy}
2. {question about team/culture}
3. {question about role's impact}
- **Topics to handle carefully:** {any sensitive items}Step 5: Save
Write to data/research/{company-slug}.md.
"Research saved. You can reference it anytime.
Want me to:
- Draft outreach to one of these contacts?
- Evaluate a role at this company? Paste the job posting.
- Prepare interview stories specific to this company?"
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

