Agent skill

Tech Presentation Interview

by curiositech in curiositech/some_claude_skills

Prepares for "reverse system design" rounds where you present YOUR past technical work.

MITAuto-check passedBusiness, Finance & HR

Install Tech Presentation Interview

skills CLI
$ npx skills add curiositech/some_claude_skills --skill tech-presentation-interview -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install curiositech/some_claude_skills tech-presentation-interview --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/curiositech/some_claude_skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/tech-presentation-interview .claude/skills/tech-presentation-interview && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tech-presentation-interview
GitHub stars
243
Token cost
~3.6k tokens
SKILL.md length
1,608 words
Files
4 (incl. references)
Skills in repo
109
Repo updated
First seen
Licence
MIT

At a glance

Prepares for "reverse system design" rounds where you present YOUR past technical work.

  • Works in 5 steps: Solo run-through (3x minimum): Present… → Record yourself: Watch the recording.… → Peer mock (2x minimum): Present to a… → …
  • Project selection
  • SKILL.md covers When to Use, Project Selection, Narrative Arc Framework and Depth Calibration, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Tech Presentation Interview is an agent skill from curiositech/some_claude_skills. Prepares for "reverse system design" rounds where you present YOUR past technical work. Use for project selection, narrative arc structuring, whiteboard diagrams, depth calibration, and hostile Q&A handling. Activate on "tech presentation", "present your work", "reverse system design", "project deep dive". NOT for designing hypothetical systems, resume writing, or career narrative extraction.

Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `.claude-plugin/plugin.json`, `references/project-narrative-template.md` and `references/whiteboard-diagrams.md`).

It sits in Business, Finance & HR, covering Performance reviews, Diagrams and Resume and CV writing. The repository describes itself as: Claude skills that make my life easier. The licence is MIT.

When your agent uses it

  • Project selection
  • Narrative arc structuring
  • Whiteboard diagrams
  • Depth calibration

Example prompts

  • “reverse system design”
  • “tech presentation”
  • “present your work”
  • “/tech-presentation-interview”

Requirements

  • Pre-approved tools (allowed-tools): Read, Write, Edit

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Solo run-through (3x minimum): Present to an empty room, timed. Target: 20-25 min for the structured portion, leaving 15-20 min for Q&A.
  2. Record yourself: Watch the recording. Note filler words, hand-waving over gaps, and moments where you lose the thread.
  3. Peer mock (2x minimum): Present to a technical friend. Have them play hostile questioner. Track which questions you fumble.
  4. Q&A stress test: Have someone rapid-fire 10 questions from the hostile questions list. Practice composure under pressure.
  5. Timing gate: If your structured presentation exceeds 25 min in rehearsal, cut content. You WILL run longer in the real thing.

What it can do on your machine

Read from SKILL.md and the folder at commit 6713fc7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are mermaid).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tech Presentation Interview loads about 3.6k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 106 tokens; SKILL.md has 1,608 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~106
When it runs · the whole SKILL.md, loaded when a task matches
~3.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from curiositech/some_claude_skills at commit 6713fc7, republished under its MIT licence (© curiositech). 1,608 words, ~3,567 tokens.

Download SKILL.mdSave it as .claude/skills/tech-presentation-interview/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
tech-presentation-interview
description
Prepares for "reverse system design" rounds where you present YOUR past technical work. Use for project selection, narrative arc structuring, whiteboard diagrams, depth calibration, and hostile Q&A handling. Activate on "tech presentation", "present your work", "reverse system design", "project deep dive". NOT for designing hypothetical systems, resume writing, or career narrative extraction.
allowed-tools
Read, Write, Edit
metadata.gated
true
metadata.category
Career & Interview
metadata.tags
interview, presentation, system-design, storytelling

Tech Presentation Interview

The tech presentation round is a reverse system design: instead of designing a hypothetical system on a whiteboard, you present a real system YOU built. This tests three things no other round can: genuine depth of understanding, ability to communicate complex ideas under pressure, and authentic ownership versus inherited knowledge.

When to Use

Use for:

  • Selecting which project to present from your career
  • Structuring a 25-45 minute technical presentation with narrative arc
  • Calibrating depth -- which components to go deep on, which to skim
  • Preparing whiteboard/virtual-board diagrams with progressive disclosure
  • Rehearsing answers to hostile follow-up questions
  • Adapting presentation to different audience compositions (researchers, engineers, managers)

NOT for:

  • Designing a system you haven't built (use ml-system-design-interview)
  • Writing your resume or extracting career stories (use cv-creator or career-biographer)
  • Coordinating across multiple interview rounds (use interview-loop-strategist)
  • Practicing coding problems or behavioral STAR stories
  • Conference talk preparation (different format, different evaluation criteria)

Project Selection

The most common failure mode is choosing the wrong project. Use this decision tree:

mermaid
flowchart TD
    A[List your top 5 projects] --> B{Did YOU make key<br/>technical decisions?}
    B -->|No, I inherited it| SKIP[Skip this project]
    B -->|Yes| C{Can you explain<br/>alternatives you rejected?}
    C -->|No, I just used<br/>what was standard| SKIP
    C -->|Yes, I evaluated<br/>tradeoffs| D{Are there interesting<br/>failure modes or<br/>unexpected challenges?}
    D -->|It went smoothly| WEAK[Weak choice --<br/>no drama = no depth]
    D -->|Yes, things broke<br/>or surprised us| E{Can you fill 30+ min<br/>of technical depth<br/>on 2-3 components?}
    E -->|No, it was<br/>straightforward| WEAK
    E -->|Yes| F{Is it relevant to<br/>the target role?}
    F -->|Not really| BACKUP[Keep as backup --<br/>use if nothing<br/>better qualifies]
    F -->|Yes, strong match| PICK[Strong candidate --<br/>select this project]
Selection Criteria Scorecard

Rate each candidate project 1-5:

CriterionWeightWhat to evaluate
Personal ownership5xYOUR decisions, not team consensus or inherited architecture
Technical complexity4xNon-obvious tradeoffs, scale challenges, algorithmic depth
Interesting failures4xThings that broke, surprises, pivots, lessons learned
Relevance to role3xOverlaps with what the target team builds
Quantified impact2xMetrics you can cite (latency, throughput, revenue, accuracy)
Recency1xMore recent is better, but a great 5-year-old project beats a boring recent one

Threshold: Total score > 60 = strong choice. 40-60 = acceptable if nothing better. < 40 = find another project.


Narrative Arc Framework

Every great presentation follows this structure. Deviations lose the audience.

mermaid
flowchart LR
    CTX["Context<br/&gt;2 min"] --> PROB["Problem<br/&gt;3 min"]
    PROB --> WHY["Approach & Why<br/&gt;5 min"]
    WHY --> ARCH["Architecture Deep Dive<br/&gt;10 min"]
    ARCH --> RES["Results & Impact<br/&gt;3 min"]
    RES --> CHANGE["What I Would Change<br/&gt;2 min"]
    CHANGE --> QA["Q&A<br/&gt;15+ min"]
Phase Details

1. Context (2 min) -- Set the stage. Who was the user? What was the business? Why did this matter?

  • One sentence on the company/team
  • One sentence on the user problem
  • One sentence on the scale (requests/sec, data volume, user count)
  • Do NOT start with "I built a service that..." -- start with the PROBLEM

2. Problem (3 min) -- What made this HARD? Not what you built, but why it was non-trivial.

  • Constraints that created tension (latency vs accuracy, cost vs reliability)
  • Why existing solutions didn't work
  • What would happen if you got it wrong (consequences = stakes)

3. Approach & Why (5 min) -- Decision-making process, not just the decision.

  • 2-3 alternatives you considered and WHY you rejected each
  • The key insight or constraint that drove your choice
  • What you were optimizing for (and what you knowingly sacrificed)

4. Architecture Deep Dive (10 min) -- Go deep on 2-3 components. NOT a tour of every box.

  • Start with 3-box overview on whiteboard (see references/whiteboard-diagrams.md)
  • Pick 2-3 technically interesting components to zoom into
  • For each deep component: what it does, why it's designed that way, what breaks if you change it
  • Progressive disclosure: add detail only when relevant or asked

5. Results & Impact (3 min) -- Quantified outcomes.

  • Before/after metrics (latency, throughput, accuracy, cost, developer hours)
  • Business impact (revenue, users, customer satisfaction)
  • Team impact (adoption, developer experience, operational burden)

6. What I Would Change (2 min) -- The most important 2 minutes.

  • 1-2 specific technical decisions you'd reverse with hindsight
  • Why you made the original decision (it was rational at the time)
  • What you learned that changed your thinking
  • This section builds more credibility than all your wins combined

7. Q&A (15+ min) -- Where the real evaluation happens.

  • See "Handling Deep Follow-Ups" section below

Depth Calibration

The cardinal sin is covering everything at surface level. Pick 2-3 layers to go DEEP.

Component TypeSkim (1-2 sentences)Medium (2-3 min)Deep (5+ min)
Standard infra (load balancer, CDN)Almost always skimOnly if custom configNever unless this IS the project
Data storage layerIf standard SQL/NoSQLIf sharding, replication, or hybridIf you designed the storage engine
ML model architectureIf off-the-shelfIf fine-tuned or modifiedIf custom architecture or novel approach
Data pipelineIf standard ETLIf real-time or complex transformsIf you solved a hard data quality problem
API/interface designIf REST/GraphQL standardIf complex versioning or contractsIf protocol design was the core challenge
Monitoring/observabilityUsually skimIf anomaly detection is coreIf this IS the system

Rule of thumb: Go deep on the parts where YOU made a non-obvious decision. Skim the parts where you used an industry-standard tool in the standard way.


Handling Deep Follow-Ups

The Q&A is where interviewers separate builders from bystanders. Prepare for these patterns:

"Tell me more about X"
  • This is an invitation, not a trap. Go one level deeper on implementation.
  • Structure: "The key challenge with X was [constraint]. We solved it by [approach] because [reason]. The tricky part was [non-obvious detail]."
  • If you genuinely don't remember a detail: "I'd need to check the specifics, but the design principle was [principle] and the implementation followed [pattern]."
"Why didn't you use [alternative]?"
  • Never dismiss the alternative. Acknowledge its strengths first.
  • Structure: "We considered [alternative]. It's strong for [use case]. We chose [our approach] because in our context, [specific constraint] made [alternative] less suitable. Specifically, [concrete reason with numbers if possible]."
  • If you hadn't considered it: "That's a good option I hadn't evaluated at the time. Based on what I know now, the key tradeoff would be [tradeoff]. I think for our constraints, [assessment]."
"That seems over-engineered"
  • Don't get defensive. Restate the constraint that justified the complexity.
  • Structure: "I understand that reaction. The complexity was driven by [specific requirement]. Without [the complex part], we would have hit [concrete failure mode]. That said, if [requirement] changes, I'd simplify by [specific simplification]."
"What would you do differently?"
  • NEVER say "nothing." This is the most important question.
  • Prepare 2-3 specific technical changes with reasoning.
  • Structure: "Knowing what I know now, I'd change [specific decision]. At the time, [why it was rational]. Since then, [what changed -- new tooling, learned lesson, scale changed]. The new approach would be [specific alternative]."
Show full SKILL.md (635 more words)Show less
"What's the failure mode?"
  • Describe actual failures that happened, not hypotheticals.
  • Structure: "The primary failure mode is [X]. We hit it [frequency]. When it happens, [impact]. Our mitigation is [approach]. The residual risk is [what's still unprotected]."

Audience Calibration

Adjust depth based on who's in the room:

AudienceEmphasizeDe-emphasize
Researchers / scientistsNovel approaches, evaluation methodology, ablation studiesInfra details, deployment ops
Backend / systems engineersScale, reliability, performance tradeoffs, failure handlingML model internals, business context
ML engineersModel architecture, training pipeline, data challenges, serving infraBusiness impact, team dynamics
Engineering managersDecision-making process, team coordination, technical risk managementLow-level implementation details
Mixed panelStart broad, let Q&A reveal where each panelist wants depthDon't pre-optimize for one audience

Anti-Patterns

Demo Reel

Novice: Presents all wins, no failures or trade-offs. Every decision was optimal. The system performed beautifully from day one. Metrics only go up and to the right. Expert: Proactively discusses what didn't work, what surprised them, and what they'd change. Treats failures as evidence of genuine engagement, not embarrassment. Shares specific metrics for both successes AND shortcomings. Detection: When asked "what would you do differently?" the answer is vague ("maybe better testing") or unconvincing ("honestly, I'm pretty happy with how it turned out"). No failure stories surface organically during the presentation.

Team Credit Confusion

Novice: Uses "we" for everything. "We designed the architecture." "We chose Kafka." "We solved the latency problem." Unclear what THEY specifically did versus what the team did collectively versus what a teammate owned entirely. Expert: Clear ownership markers throughout: "I led the design of the serving layer, collaborated with our data team on the pipeline, and my teammate Sarah owned the model training infrastructure. Let me focus on the serving layer since that was my primary contribution." Uses "I" for decisions they drove, "we" for genuine collaboration, and names teammates for their contributions. Detection: Under follow-up questioning, cannot explain specific technical decisions in detail. When asked "why Kafka over RabbitMQ?", answers with "that was the team's decision" or gives a generic textbook comparison rather than the specific evaluation they ran.

Architectural Tourism

Novice: Covers every component at surface level. "And then we had a cache, and a queue, and a database, and a load balancer, and a model server, and a feature store..." Each component gets 1-2 sentences. Runs out of time before reaching anything interesting. The whiteboard looks like a busy subway map. Expert: Draws the 3-box overview, explicitly says "I'm going to focus on two components where the interesting engineering happened," and goes DEEP. Spends 5 minutes on one component explaining the tradeoffs, alternatives considered, failure modes, and what they learned. The interviewer leaves understanding that component thoroughly. Detection: Presentation runs over time. All component descriptions are surface-level. Whiteboard has 15+ boxes with no zoom-in area. When asked to go deeper on any single component, the candidate has nothing beyond what they already said.


Rehearsal Protocol

  1. Solo run-through (3x minimum): Present to an empty room, timed. Target: 20-25 min for the structured portion, leaving 15-20 min for Q&A.
  2. Record yourself: Watch the recording. Note filler words, hand-waving over gaps, and moments where you lose the thread.
  3. Peer mock (2x minimum): Present to a technical friend. Have them play hostile questioner. Track which questions you fumble.
  4. Q&A stress test: Have someone rapid-fire 10 questions from the hostile questions list. Practice composure under pressure.
  5. Timing gate: If your structured presentation exceeds 25 min in rehearsal, cut content. You WILL run longer in the real thing.

Reference Files

FileConsult When
references/project-narrative-template.mdStructuring a project presentation from scratch; filling out the narrative arc; preparing Q&A answers; worked example of an ML pipeline presentation
references/whiteboard-diagrams.mdPlanning what to draw during the presentation; progressive disclosure strategy; physical and virtual whiteboard tips; common diagram patterns for ML systems

© curiositech, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in .claude/skills/tech-presentation-interview of curiositech/some_claude_skills.

  • SKILL.md
  • .claude-plugin/plugin.json
  • references/project-narrative-template.md
  • references/whiteboard-diagrams.md

Open the folder on GitHubat commit 6713fc7

Compare with similar skills

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Binary Trees InterviewerPrepLabsAI/InterviewMentor112—~2.4kAutomated safety check: PassMIT
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Make FiguresAperivue/medsci-skills329—~8.4kAutomated safety check: PassMIT

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Questions about Tech Presentation Interview

What does Tech Presentation Interview do?

Prepares for "reverse system design" rounds where you present YOUR past technical work. Tech Presentation Interview is an agent skill from curiositech/some_claude_skills. Prepares for "reverse system design" rounds where you present YOUR past technical work.

When should I use Tech Presentation Interview?

Tech Presentation Interview fits situations like: project selection; narrative arc structuring; whiteboard diagrams; depth calibration.

How do I install Tech Presentation Interview in Claude Code?

Run `npx skills add curiositech/some_claude_skills --skill tech-presentation-interview -a claude-code`. Or copy the skill folder (.claude/skills/tech-presentation-interview in curiositech/some_claude_skills) into .claude/skills/tech-presentation-interview in your project. Claude Code loads it when a task matches its description.

How do I install Tech Presentation Interview in Codex?

Run `npx skills add curiositech/some_claude_skills --skill tech-presentation-interview -a codex`. Or copy the skill folder (.claude/skills/tech-presentation-interview in curiositech/some_claude_skills) into .agents/skills/tech-presentation-interview in your project. Codex loads it when a task matches its description.

Can I use Tech Presentation Interview in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add curiositech/some_claude_skills --skill tech-presentation-interview -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tech-presentation-interview, .gemini/skills/tech-presentation-interview, .github/skills/tech-presentation-interview and .opencode/skills/tech-presentation-interview in your project.

What does Tech Presentation Interview need to run?

SKILL.md names no scripts, command-line tools or credentials: Tech Presentation Interview is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit.

Does Tech Presentation Interview access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Tech Presentation Interview safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tech Presentation Interview use?

Tech Presentation Interview is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tech Presentation Interview use?

About 3.6k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.5k tokens, read only when the agent opens those files.

What are the alternatives to Tech Presentation Interview?

Skills that share tags, products or a category with Tech Presentation Interview: Backend and Agent Project Selector (lishuangqiang/backend-agent-resume-scout, 347 stars), Binary Trees Interviewer (PrepLabsAI/InterviewMentor, 112 stars), Nextjs React Expert (Dokhacgiakhoa/Agent-Skills-4-Vibe-Coding-CLI, 507 stars) and Deep Analysis (nicepkg/auto-company, 192 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tech Presentation Interview?

curiositech (a GitHub organization) maintains it in curiositech/some_claude_skills, which has 243 GitHub stars. The repository holds 109 skills in this directory. The repository was last updated on September 6, 2026.

Source: curiositech/some_claude_skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.