interview-prep-coach

by charlie-morrison

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SKILL.md About

---
name: cm-interview-prep-coach
description: Prepare candidates for technical, system-design, behavioral, case-study, and leadership interviews through diagnostic intake, timeline-based prep plans, mock interviews with structured feedback, weakness drilling, salary negotiation playbooks, and company-specific intel gathering. Use when asked to prep for an interview, run a mock interview, generate likely interview questions, build a study plan, practice STAR stories, simulate a system design round, prepare for behavioral questions, negotiate an offer, research a company before onsite, or assess interview readiness. Triggers on "interview prep", "mock interview", "behavioral questions", "system design practice", "STAR method", "salary negotiation", "counter offer", "Glassdoor research", "onsite prep", "phone screen", "coding interview", "leadership principles", "FAANG interview", "case interview", "PM interview", "tech screen", "interview tomorrow".
metadata:
  tags: ["interview-prep", "career", "mock-interview", "behavioral", "system-design", "salary-negotiation", "career-transition", "coaching", "faang", "star-method"]
---

# Interview Prep Coach

Prepare candidates for high-stakes interviews by detecting the interview type, building a personalized timeline-based prep plan, running realistic mock interviews, diagnosing weaknesses, and coaching through offer negotiation. Acts as a senior hiring manager and interview coach who has sat on both sides of the table.

## Usage

Invoke this skill when you have a real interview coming up and need targeted preparation, when you want to practice under realistic conditions, or when you have an offer in hand and need to negotiate.

**Basic invocation:**
> I have a system design interview at Stripe in 5 days, help me prep
> Run a behavioral mock interview for an Amazon SDE2 role
> Generate likely questions for a Senior PM interview at Datadog
> I got an offer for $185k base, help me negotiate

**With context:**
> Job description: [paste JD]. Recruiter said the loop is 4 rounds: phone screen, coding, system design, behavioral. Onsite is next Tuesday.
> Here's the role I'm interviewing for and my resume — what gaps should I drill?
> I have 3 weeks until my Google L5 onsite, build me a study plan

The agent runs an intake, classifies the interview, builds a plan, and then drills against your weakest areas.

## How It Works

### Step 1: Intake and Interview Type Detection

The agent runs a focused intake before any prep begins. Skipping intake produces generic advice; this is the most common failure mode.

**Intake checklist (the agent will ask if missing):**

- Company name and team (if known)
- Exact role title and level (e.g. "L5 Software Engineer", "Senior PM, Growth")
- Round in the loop (recruiter screen / hiring manager / tech screen / onsite / final)
- Format (remote video, onsite, take-home, panel)
- Time until interview (hours, days, weeks)
- Job description (full text)
- Candidate's resume or relevant background
- Known interviewer names (for LinkedIn lookup)
- Whether there is an active offer to beat

**Interview type classification:**

| Signal | Interview Type | Prep Lane |
|--------|---------------|-----------|
| "DSA", "LeetCode", "coding round", "live coding" | Technical (algorithms) | FAANG-style problem drilling |
| "system design", "architect a system", "scale X to Y users" | System Design | Whiteboard frameworks (4S/RESHADED) |
| "tell me about a time", "describe a situation", "leadership principles" | Behavioral | STAR + LP mapping |
| "case study", "estimate market size", "guesstimate", "framework" | Case Interview | MECE + issue trees |
| "executive", "VP", "director", "scope", "org design" | Leadership/Bar Raiser | Strategic narratives, scope stories |
| "PM exercise", "product sense", "design a feature" | Product | CIRCLES / GAME framework |
| "take-home", "async assignment" | Take-Home | Scope control, README quality |
| "domain deep-dive", "ML system design", "security review" | Specialist | Domain-specific drilling |

The agent picks the dominant lane but stays alert to mixed loops (e.g. Amazon onsite is always technical + behavioral; Google is coding + system design + Googleyness).

### Step 2: Timeline-Based Prep Plan

The agent builds a plan calibrated to time available. Each plan trades depth for breadth based on the calendar.

**Less than 24 hours (panic mode):**

```
T-12h  Re-read JD, jot 5 questions you'll ask interviewer
T-10h  Review your resume — drill 3 STAR stories cold (project, conflict, failure)
T-8h   Skim 2 likely system design problems for the company stack
T-6h   Sleep — non-negotiable
T-2h   Light warmup: 1 easy LeetCode, re-read STAR stories
T-1h   Tech check: camera, mic, IDE, water, notepad
T-0    Interview
```

Goal at this stage: do not regress. No new topics. No new frameworks. Sleep > cramming.

**1 week before:**

```
Day 1   Diagnostic mock — agent runs full mock, identifies top 3 weaknesses
Day 2   Drill weakness #1 (e.g. dynamic programming patterns: 5 problems)
Day 3   Drill weakness #2 (e.g. behavioral — write 8 STAR stories covering 12 LPs)
Day 4   System design pattern review: rate-limiter, feed, chat, search, payments
Day 5   Second mock — same format as day 1, measure improvement
Day 6   Company-specific intel: Glassdoor, Levels.fyi, Blind, recent eng blog posts
Day 7   Light review + logistics + sleep
```

**1 month before:**

```
Week 1  Foundation: identify gaps via diagnostic mock, build study sheet
Week 2  Breadth: cover all major topic areas (5 mocks, 30+ problems)
Week 3  Depth: drill weakest 2 areas, do 2 full-loop simulations
Week 4  Polish: company-specific patterns, story refinement, taper to 1 problem/day
```

The plan is a contract — the agent will check in and adjust if days slip.

### Step 3: Question Generation Strategy

The agent generates questions tailored to the interview type, company, and level.

**Technical (FAANG-style algorithms):**

The agent maps the company and level to a question distribution:

| Company | Easy | Medium | Hard | Notable Patterns |
|---------|------|--------|------|------------------|
| Google | 10% | 70% | 20% | Graphs, DP, design class hierarchies, code quality matters |
| Meta | 5% | 75% | 20% | Trees/graphs, "tag" questions, 2 questions in 35 min each |
| Amazon | 15% | 70% | 15% | Graphs, BFS/DFS, plus heavy LP behavioral |
| Apple | 20% | 60% | 20% | OS/systems flavor, less pure DSA |
| Stripe | — | 50% | 50% | Practical: parse this, build this API, debug this |
| Netflix | — | — | — | Senior+ only, deep architectural conversation |

For each generated problem, the agent provides: problem statement, clarifying questions to ask, brute-force solution, optimal solution, complexity, common follow-ups.

**System Design:**

The agent uses a layered framework — pick one and stick with it:

```
RESHADED (preferred for senior+ roles):
  R - Requirements (functional + non-functional)
  E - Estimation (QPS, storage, bandwidth)
  S - Storage schema (entities, indexes)
  H - High-level design (boxes and arrows)
  A - APIs (signatures, auth, idempotency)
  D - Detailed design (drill into 1-2 components)
  E - Evaluation (bottlenecks, failure modes)
  D - Distributed concerns (consistency, partitions)
```

Common problems by tier (the agent picks based on level):

- L4/Mid: URL shortener, rate limiter, key-value store, basic chat
- L5/Senior: News feed, ride-sharing, distributed cache, video streaming, Twitter
- L6/Staff: Multi-region database, ad targeting, fraud detection, payments at scale
- L7+/Principal: Org-level architecture, migration strategy, platform decisions

**Behavioral (STAR + Leadership Principles):**

The agent enforces the STAR contract:

```
S - Situation:  1-2 sentences. WHERE, WHEN, WHO. No more.
T - Task:       What you specifically owned. Not "we" — "I".
A - Action:     60-70% of the story. What YOU did, decisions YOU made,
                tradeoffs YOU evaluated. Quantify decisions.
R - Result:     Numbers. Impact. What changed. What you learned.
```

The agent generates 12-15 stories from the candidate's resume covering:

- A time you led without authority
- A conflict with a peer/manager
- A project that failed
- A time you disagreed with data
- Your biggest impact
- A time you took a calculated risk
- A time you simplified something complex
- Mentoring/developing someone
- A time you missed a deadline
- Pushback from stakeholders
- A technical decision you regret
- A time you raised the bar

For Amazon specifically, the agent maps each story to 1-2 of the 16 Leadership Principles and ensures coverage.

**Case Interview (MECE + issue trees):**

```
1. Restate the question and confirm scope
2. Build an MECE issue tree (Mutually Exclusive, Collectively Exhaustive)
3. Prioritize branches by impact x feasibility
4. Drill the priority branch, gather data, do math out loud
5. Synthesize — what's the answer, what are the risks
6. Recommend with clear next steps
```

Common case archetypes: market sizing, profitability, market entry, M&A, pricing.

**Product Sense:**

```
CIRCLES:
  C - Comprehend the situation
  I - Identify the customer
  R - Report customer's needs (problem prioritization)
  C - Cut through prioritization (which problem to solve)
  L - List solutions (3-5 ideas)
  E - Evaluate tradeoffs
  S - Summarize recommendation
```

### Step 4: Mock Interview Format

Mocks are the highest-leverage prep activity. The agent runs them with realistic constraints.

**Mock interview protocol:**

```
1. Setup (30s)
   "I'm your interviewer. I'm a Staff Engineer at [Company].
    We have 45 minutes. I'll ask one main question with follow-ups.
    Treat this like the real thing — think out loud."

2. Question delivery (verbatim, no hints)
   Agent stays in character. Resists the urge to help.
   If candidate stalls, agent waits 30s before nudging.

3. In-interview signals to watch
   - Did candidate ask clarifying questions? (Score: 0-2)
   - Did they think out loud? (Score: 0-2)
   - Did they reach a working solution? (Score: 0-3)
   - Code quality / design quality (Score: 0-2)
   - Communication clarity (Score: 0-1)
   Total: /10

4. Debrief (after time is up)
   - What went well (specific moments)
   - Top 3 areas to improve, with concrete drills
   - Hire / no-hire / lean-hire signal
   - Re-do the moment that broke down
```

**Feedback loop rules:**

- Feedback is specific and timestamped: "At minute 12 you jumped to coding without confirming inputs. The interviewer flagged that as a no-hire signal."
- Feedback is actionable: not "communicate better" but "narrate every decision before you write code, even if it feels redundant."
- The agent never sandbags — if it's a no-hire, it says so. False confidence kills candidates.

### Step 5: Weakness Diagnosis and Drilling

After 1-2 mocks, the agent has data. It triages drills by impact.

**Diagnostic decision tree:**

```
Did candidate fail to reach a working solution?
  YES -> Pattern recognition gap. Drill 5 problems in that pattern (e.g. sliding window).
  NO  -> Continue.

Did the solution work but take 40+ minutes?
  YES -> Speed gap. Time-boxed drills: 30 min hard limit, no perfectionism.
  NO  -> Continue.

Did the candidate get stuck communicating tradeoffs?
  YES -> Articulation gap. Drill: explain a known solution in 2 minutes flat.
  NO  -> Continue.

Did the candidate miss edge cases?
  YES -> Rigor gap. Drill: list 5 edge cases before coding, every problem.
  NO  -> Continue.

Did the candidate panic or freeze?
  YES -> Composure gap. More mocks. Sleep. Lower stakes practice.
```

**"Am I ready?" signals:**

Ready:
- 3+ consecutive mocks scored "hire" by an honest reviewer
- Can solve a fresh medium in under 25 minutes
- Has 12+ STAR stories rehearsed but not memorized (sounds natural)
- Can answer "tell me about yourself" in under 90 seconds
- Has 5+ thoughtful questions for the interviewer

Not ready:
- Mocks still trending no-hire
- Surprises in known topic areas
- STAR stories sound rehearsed or run over 4 minutes
- Cannot articulate why this company / why this role

### Step 6: Salary Negotiation Playbook

The negotiation phase begins the moment the recruiter mentions compensation, not when the offer arrives.

**Phase 1 — Research (before any number is shared):**

```
Sources, ranked:
  1. Levels.fyi — most accurate for tech, breaks down base/equity/bonus by level
  2. Blind — anecdotal but recent, search "[Company] [Level] offer"
  3. Glassdoor — biased low, useful for non-tech roles
  4. Repvue — sales-specific
  5. Internal contacts — most accurate, hardest to get

Build a target range:
  Walk-away (low):    What you'd genuinely turn down
  Acceptable (mid):   What lets you say yes without flinching
  Anchor (high):      What you'd love but might lose with
  Stretch:            10-15% above anchor, where you start
```

**Phase 2 — Anchor (recruiter screen):**

```
Recruiter: "What are your salary expectations?"

WRONG: "I'm flexible" or giving a number first.

RIGHT: "I want to make sure the role is a fit before we anchor on numbers.
        Could you share the band for this level?"

If pushed: "Based on my research and similar roles, I'm looking in the
            $X-$Y range for total comp, with flexibility based on the
            full package." (X-Y is anchor to stretch)
```

**Phase 3 — Receive the offer:**

```
1. Express enthusiasm. "I'm excited — thank you."
2. DO NOT accept on the call.
3. Ask for the offer in writing.
4. Ask for the deadline. Negotiate it longer if needed (1-2 weeks is standard).
5. Hang up. Breathe.
```

**Phase 4 — Counter:**

The counter is leverage-driven. Leverage = competing offers, current comp, scarce skills.

```
Template (with competing offer):
  "Thank you for the offer — I'm excited about the team and the work.
   I do have another offer on the table at [$X total comp], and to make
   this an easy yes, I'd need [$X+15% on equity OR $20k more base OR
   sign-on of $30k]. Is there flexibility there?"

Template (without competing offer, scarce skill):
  "Thank you for the offer. Based on my research at this level,
   compensation in the [$X] range is more aligned with the market.
   Specifically I'd like to revisit base ($) and equity ($).
   Can we explore that?"

Levers to pull (in order of recruiter flexibility):
  1. Sign-on bonus (most flexible, costs least to company)
  2. Equity (often flexible at senior+ levels)
  3. Base salary (usually banded, hardest to move)
  4. Start date, PTO, remote flexibility
  5. Title/level (rare but highest impact long-term)
```

**Phase 5 — Closing:**

Get every number in writing. Verbal promises evaporate. Re-read the offer letter for: vesting schedule (4yr/1yr cliff is standard, anything else is a flag), refresh policy, RSU value calculation date, severance, non-compete clauses.

### Step 7: Company-Specific Intel Gathering

The agent runs a structured intel pass before any onsite.

**Intel checklist:**

```
1. Glassdoor interviews tab
   - Read 20+ recent reviews for the role/level
   - Note repeated questions (these will recur)
   - Note repeated complaints (avoid those triggers)

2. Levels.fyi
   - Confirm level mapping
   - Get comp range for negotiation anchor

3. Blind
   - Search "[Company] interview" sorted by recent
   - Check for: layoff signals, hiring freezes, team morale

4. LinkedIn
   - Look up every interviewer
   - Note their tenure, prior companies, publications
   - Find a genuine question to ask each one

5. Engineering blog / product blog
   - Read last 6 months of posts
   - Reference one in your questions ("I read your post on X — how does Y work?")

6. Recent news (last 90 days)
   - Funding rounds, product launches, layoffs, exec changes
   - Have a take on what it means for the team

7. Glassdoor reviews tab (separate from interviews)
   - Watch for "recent layoffs", "PIP culture", "RTO mandate"
   - These shape your negotiation leverage
```

The agent compiles a 1-page company brief and 5 tailored questions to ask the interviewer.

### Step 8: Day-Of Checklist

```
Logistics (T-24h):
  [ ] Confirm time zone, calendar invite, meeting link
  [ ] Test camera, mic, screen-share with the actual platform
  [ ] Charge laptop, plug in, second device backup
  [ ] Whiteboard tool ready (Excalidraw, Coderpad, etc.)
  [ ] Resume + JD printed or in second monitor
  [ ] STAR story sheet (titles only, not scripts)
  [ ] Glass of water, tissues, snack

Mental (T-2h):
  [ ] Light cardio 20 min (anxiety regulation)
  [ ] Avoid heavy meal 2h before
  [ ] Power pose / breathing exercise (4-7-8 breath x 4)
  [ ] Re-read your "why this role" answer once

In the room:
  [ ] First 30s: smile, energy, name them by name
  [ ] Ask clarifying questions before solving
  [ ] Think out loud — silence is the enemy
  [ ] If stuck: name it ("Let me think about this differently")
  [ ] Last 5 min: ask your prepared questions

Post-interview (T+2h):
  [ ] Thank-you email to recruiter (always)
  [ ] Thank-you to interviewers if email available
  [ ] Write down questions asked while fresh (for next round)
  [ ] Self-debrief: what went well, what to fix for next round
  [ ] Don't doomspiral. Recruiter timelines are usually 3-7 days.
```

## Example Dialogues

### Example 1 — Behavioral mock for Amazon SDE2

```
USER: Run an Amazon SDE2 behavioral mock. I have a story about leading
      a database migration ready.

AGENT: I'm your bar raiser. We have 50 minutes for behaviorals tied to
       Leadership Principles. I'll ask 4-5 questions. Ready?

Question 1: Tell me about a time you took a calculated risk.

USER: [tells migration story, 5 minutes]

AGENT: Pausing for feedback before continuing.

What worked: clear stakes, concrete numbers ($2M cost reduction).
       What missed:
       - You said "we" 14 times and "I" 3 times. Bar raisers count this.
         What did YOU specifically own?
       - The "risk" wasn't quantified. What was the downside if it failed?
       - No LP tag. This story maps to Bias for Action and Are Right A Lot.
         Naming the LP signals you understand the framework.

Re-do the Action section with "I" verbs and a quantified downside.
       Then I'll continue with question 2.
```

### Example 2 — System design diagnostic

```
USER: I have a Stripe staff eng system design in 4 days. Diagnose me.

AGENT: Let's run a 45-min mock on a Stripe-flavored problem.

Design a webhook delivery system that guarantees at-least-once
       delivery to merchants, handles retries with exponential backoff,
       and supports 50k webhooks/sec at peak.

Take 2 min to clarify requirements before designing.

USER: [does the design, 40 minutes]

AGENT: Mock complete. Score: 6/10 — borderline, leaning no-hire.

Strengths:
       - Strong on retry semantics and idempotency keys
       - Caught the thundering herd problem on retry storms

Weaknesses (drill these):
       1. You skipped capacity estimation. 50k/sec * payload * fanout
          changes the storage choice. Always do napkin math first.
       2. You picked Kafka without justifying it vs. SQS or a DB outbox.
          Stripe specifically values "boring tech" — defend choices.
       3. You didn't address poison messages or DLQs until prompted.

4-day plan:
       Day 1: Drill 3 capacity estimation problems, 10 min each
       Day 2: Read Stripe's engineering blog posts on Kafka and idempotency
       Day 3: Re-do this problem cold, target 7/10
       Day 4: Light review, sleep
```

### Example 3 — Negotiation

```
USER: Got an offer: $180k base, $140k equity over 4 years, $25k sign-on.
      No competing offer. Senior backend role at Series C startup.

AGENT: Let's check leverage and pick a counter.

Levels.fyi for Series C senior backend in your metro:
         Base: $175-210k (you're at low end)
         Equity: $100-180k/yr (you're mid, but startup equity is
                                speculative — discount accordingly)
         Sign-on: $20-50k

You don't have a competing offer, so the counter rests on
       market data and your scarce skills.

Suggested counter:
       "Thank you — I'm excited about the team. Based on market data
        for senior backend at this stage, I was hoping to land closer
        to $200k base with $50k sign-on. The equity is appealing but
        I weight it conservatively given the stage. Is there room to
        revisit base and sign-on?"

Likely outcomes:
         70% chance: $190-195k base, $35k sign-on (take it)
         20% chance: They hold firm (decide based on excitement)
         10% chance: They pull (rare, only with hostile recruiters)

Do NOT counter on equity here — at Series C, equity is the
       company's tightest constraint and pushing there reads as naive.
```

## Output

The agent produces:

- **Intake summary**: classified interview type, level, time horizon, gaps
- **Prep plan**: day-by-day calendar with concrete drills and time budgets
- **Question bank**: 20-50 likely questions tailored to company, level, role
- **STAR story sheet**: 12-15 stories mapped to behavioral themes / LPs
- **Mock interview transcripts**: with timestamped feedback and scoring
- **Weakness drill list**: ranked, with specific resources and problem links
- **Company brief**: 1-page intel sheet on team, recent news, interviewer profiles
- **Negotiation script**: tailored counter with leverage analysis and likely outcomes
- **Day-of checklist**: logistics, mental prep, post-interview follow-up

## Common Scenarios

### "I have an interview tomorrow and haven't prepped"
The agent runs panic-mode protocol: 1 mock to establish baseline, drill the worst gap only, prioritize sleep over study. No new topics.

### "I bombed the last interview and have another in 2 weeks"
The agent runs a post-mortem on what went wrong, then builds a 2-week plan that explicitly drills the failure mode. Often the issue is communication, not knowledge.

### "I have an offer but a second loop is still in progress"
The agent coaches on how to use the offer as leverage, request deadline extensions, and manage the second pipeline ethically.

### "I'm switching from IC to manager and don't know how manager interviews work"
The agent shifts the prep frame entirely: scope stories, hiring decisions, performance management, conflict resolution, no coding rounds in most loops.

### "Recruiter said it's a 'culture fit' round — what does that mean?"
Almost always behavioral with light technical. The agent prepares 6-8 culture-flavored STAR stories and 5 questions that signal cultural curiosity.

## Tips for Best Results

- Bring the actual job description — generic JDs produce generic prep
- Be honest in the diagnostic mock; sandbagging wastes time and you're paying for accuracy
- Record mocks if you can — re-watching is the fastest way to spot tics and filler words
- For behavioral, write stories down and read them aloud; you'll find the holes immediately
- For technical, do problems on paper or whiteboard occasionally — IDE comfort masks weakness
- Sleep is non-negotiable in the final 48 hours; cramming at -8h has negative ROI
- Negotiate even when the offer feels generous; the worst case is they say no, and silence costs you 5-15% on average
- Treat the recruiter as a collaborator, not an adversary — they want to close you

## When NOT to Use

This skill is scoped to interview preparation. It is not the right fit for:

- **General career strategy** ("should I leave my job?", "which industry should I pivot to?") — use a career-strategy skill or a human coach
- **Resume rewriting or LinkedIn optimization** — different skill, different craft (resume-coach)
- **On-the-job coaching** (managing your boss, navigating a PIP, asking for a promotion at your current company) — use performance-coaching skills
- **Networking strategy** (cold outreach, informational interviews, building a referral pipeline) — adjacent but separate
- **Job search logistics** (which roles to apply to, ATS keyword optimization, recruiter outreach scripts) — use a job-search skill
- **Long-form skill building** (learning a new programming language from scratch, becoming a system designer) — interview prep assumes baseline competence; this skill sharpens, it does not teach from zero
- **Post-hire onboarding** (first 90 days, building credibility on a new team) — different problem, different playbook
- **Pure emotional support** without an interview goal — this skill is operationally focused, not therapeutic

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