interview-prep
Skill8 starsChanged 5 months agoMITView on GitHub
Prepares for a specific company and role by mapping likely interview rounds, audience-specific questions, proof points, STAR story gaps, and questions to ask back. Use when the user mentions interview prep, preparing for a job interview, a mock interview, behavioral questions, or practicing for an upcoming round.
56 other projects use a version of this.
Adopted by
Most recently taken up by
- fancyboi999/ai-engineering-from-scratch-zhtheir own version, first seen Nov 8, 2026
- rohitg00/ai-engineering-from-scratchtheir own version, first seen Nov 8, 2026
- nisarth/claude-skills-storetheir own version, first seen Nov 8, 2026
- eggs-gd/career-spacetheir own version, first seen Nov 8, 2026
- Gianni03/jobtracker-skillstheir own version, first seen Nov 8, 2026
- ong6/skillstheir own version, first seen Nov 5, 2026
Used with
Projects with it also use application-tracker, interview-debrief 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.
xiding-codeSkillapplication-tracker
Automatically log and track all job applications submitted. Use this skill after every application submission to record the details in a tracking spreadsheet and save relevant documents. Also trigger when the user asks "application status", "what have I applied to", "tracking", or wants to review their application history. Maintains a single source of truth for all job search activity.
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jackhendonSkillinterview-debrief
Structure notes from a user research session into a clean debrief with insights, quotes, and implications. Paste your raw notes in and get a formatted summary ready for Notion.
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proficientlyjobsSkilljob-search
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claude-office-skillsSkillcover-letter
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xiding-codeSkillcover-letter-writer
Write and iteratively refine cover letters using a 3-agent debate team (2 Opus critics + 1 Sonnet judge). Use this skill whenever a job application allows cover letter upload, whenever the user asks to write or improve a cover letter, or whenever the job-screener skill returns APPLY for a position. The must-write rule (if enabled in config) applies: if the application system has a cover letter upload field, a cover letter MUST be written. Trigger on: "write cover letter", "cover letter", any application form with a cover letter upload option, or after a job-screener APPLY decision.
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claude-office-skillsSkillcompany-research
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Other versions56 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 56
- rohitg00/ai-engineering-from-scratch★ 78ksame name
- anthropics/knowledge-work-plugins★ 35ksame name
- tinyfish-io/tinyfish-cookbook★ 2.3ksame name
- ShenSeanChen/waku-agent★ 2ksame name
- fancyboi999/ai-engineering-from-scratch-zh★ 1.3ksame name
- jerry-ai-dev/MODULAR-RAG-MCP-SERVER★ 1.2ksame name
- lan1177/interview-prep★ 92same name
- matyasstoch/david-skills★ 59same name
- muggl3mind/career-manager★ 24same name
- jaskirat1616/grok-skills★ 22same name
46 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.
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The file
Files
Interview Prep
Prepare the user for an interview at a specific company and role using their selected text, the visible page, a pasted job description, or details they provide. Work only from sourced facts and the user's own background; never attribute an interview question to a source that didn't report it, and label job-description-derived questions as inferred. Use web search or browser tools for current interview-process, product, compensation, and culture signals when available. Adapted from santifer/career-ops interview-prep and deep modes.
- Confirm the company and role. If either is missing, ask before producing a full prep pack.
- Map the likely rounds and their audiences — recruiter screen, hiring manager, peer or technical panel, and mixed panels. See references/audience-playbook.md for each audience's focus and question bank. If the schedule is unknown, say so and give the likely audiences separately.
- Map likely questions to STAR or STAR+R story prompts and draft result first answer outlines from the user's real background only. See references/star-framework.md for the outline order, headline building, and gap handling. If they haven't supplied enough stories, flag the missing topics and ask for one detail at a time.
- Suggest technical or case prep grounded in the job description, company materials, or reported process, and include questions to ask back that reference the role, team, product, or company.
- Coach disclosure per audience: lead with what lands for each interviewer while staying consistent on comp, timeline, and motivation. The per audience strategy, compensation deflection phrasing, and honesty guardrails live in references/audience-playbook.md.
Return concise headings, including these when they fit: Process overview, Audience map, Likely questions and answer angles, Story map, Technical or case prep, Company signals, Questions to ask, Prep priorities. Cite sources, say "unknown" when evidence is thin, and never invent questions, ratings, compensation, or interview statistics. Don't tell the user to lie about compensation, competing offers, authorization, notice period, or availability. If they give an interview date, add a short countdown based prep plan.
References
- references/audience-playbook.md — per audience focus, question banks, disclosure strategy, comp deflection, and honesty guardrails. Read when mapping rounds (step 2) or coaching disclosure (step 5).
- references/star-framework.md — STAR and STAR+R outlines, result first ordering, building a headline from one number, and story gap handling. Read when drafting answer angles (step 3).
Example
Request (job description on screen + a note):
Senior Product Manager at Northwind. Recruiter phone screen next week, then a hiring-manager round. JD stresses 0→1 launches and cross-functional leadership. My note: I led a payments launch but haven't written it up.
Prep:
Audience map
- Recruiter screen: motivation, timeline, location and comp fit — lead with why Northwind.
- Hiring manager: scope and first-90-days plan; tie your payments launch to their 0→1 mandate.
Likely questions and answer angles
- "Walk me through a 0→1 product you launched." (inferred from the job description) → STAR on the payments launch, result first.
Story map
- Missing detail: your payments launch has no outcome yet. What was the result — adoption, revenue, time-to-ship? Share one number and I'll build the headline.
Questions to ask
- "What does the first 0→1 win look like for this role over the next two quarters?"
Expect a comp question on the recruiter call — if you don't have a competing offer, defer: "I'm calibrating to market for this level; can you share the band?"
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