Backend and Agent Project Selector
lishuangqiang/backend-agent-resume-scout
Finds backend or AI agent projects on GitHub that are worth putting on a resume, checks them against local source and writes a Markdown resume package.
Prepares for "reverse system design" rounds where you present YOUR past technical work.
$ npx skills add curiositech/some_claude_skills --skill tech-presentation-interview -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install curiositech/some_claude_skills tech-presentation-interview --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "tech-presentation-interview" agent skill from https://github.com/curiositech/some_claude_skills/tree/main/.claude/skills/tech-presentation-interview into .claude/skills/tech-presentation-interview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tech-presentation-interview", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/curiositech/some_claude_skills/tree/main/.claude/skills/tech-presentation-interviewType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add curiositech/some_claude_skills --skill tech-presentation-interview -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install curiositech/some_claude_skills tech-presentation-interview --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/curiositech/some_claude_skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/tech-presentation-interview .agents/skills/tech-presentation-interview && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "tech-presentation-interview" agent skill from https://github.com/curiositech/some_claude_skills/tree/main/.claude/skills/tech-presentation-interview into .agents/skills/tech-presentation-interview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tech-presentation-interview", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add curiositech/some_claude_skills --skill tech-presentation-interview -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install curiositech/some_claude_skills tech-presentation-interview --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/curiositech/some_claude_skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/tech-presentation-interview .cursor/skills/tech-presentation-interview && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "tech-presentation-interview" agent skill from https://github.com/curiositech/some_claude_skills/tree/main/.claude/skills/tech-presentation-interview into .cursor/skills/tech-presentation-interview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tech-presentation-interview", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/curiositech/some_claude_skills.git --path .claude/skills/tech-presentation-interview--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add curiositech/some_claude_skills --skill tech-presentation-interview -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install curiositech/some_claude_skills tech-presentation-interview --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/curiositech/some_claude_skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/tech-presentation-interview .gemini/skills/tech-presentation-interview && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "tech-presentation-interview" agent skill from https://github.com/curiositech/some_claude_skills/tree/main/.claude/skills/tech-presentation-interview into .gemini/skills/tech-presentation-interview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tech-presentation-interview", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install curiositech/some_claude_skills tech-presentation-interviewInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add curiositech/some_claude_skills --skill tech-presentation-interview -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/curiositech/some_claude_skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/tech-presentation-interview .github/skills/tech-presentation-interview && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "tech-presentation-interview" agent skill from https://github.com/curiositech/some_claude_skills/tree/main/.claude/skills/tech-presentation-interview into .github/skills/tech-presentation-interview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tech-presentation-interview", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add curiositech/some_claude_skills --skill tech-presentation-interview -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install curiositech/some_claude_skills tech-presentation-interview --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/curiositech/some_claude_skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/tech-presentation-interview .opencode/skills/tech-presentation-interview && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "tech-presentation-interview" agent skill from https://github.com/curiositech/some_claude_skills/tree/main/.claude/skills/tech-presentation-interview into .opencode/skills/tech-presentation-interview/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tech-presentation-interview", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
tech-presentation-interviewPrepares 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. 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.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 6713fc7. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditFrom allowed-tools in the SKILL.md frontmatter.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
The full file from curiositech/some_claude_skills at commit 6713fc7, republished under its MIT licence (© curiositech). 1,608 words, ~3,567 tokens.
.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.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.
Use for:
NOT for:
ml-system-design-interview)cv-creator or career-biographer)interview-loop-strategist)The most common failure mode is choosing the wrong project. Use this decision tree:
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]Rate each candidate project 1-5:
| Criterion | Weight | What to evaluate |
|---|---|---|
| Personal ownership | 5x | YOUR decisions, not team consensus or inherited architecture |
| Technical complexity | 4x | Non-obvious tradeoffs, scale challenges, algorithmic depth |
| Interesting failures | 4x | Things that broke, surprises, pivots, lessons learned |
| Relevance to role | 3x | Overlaps with what the target team builds |
| Quantified impact | 2x | Metrics you can cite (latency, throughput, revenue, accuracy) |
| Recency | 1x | More 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.
Every great presentation follows this structure. Deviations lose the audience.
flowchart LR
CTX["Context<br/>2 min"] --> PROB["Problem<br/>3 min"]
PROB --> WHY["Approach & Why<br/>5 min"]
WHY --> ARCH["Architecture Deep Dive<br/>10 min"]
ARCH --> RES["Results & Impact<br/>3 min"]
RES --> CHANGE["What I Would Change<br/>2 min"]
CHANGE --> QA["Q&A<br/>15+ min"]1. Context (2 min) -- Set the stage. Who was the user? What was the business? Why did this matter?
2. Problem (3 min) -- What made this HARD? Not what you built, but why it was non-trivial.
3. Approach & Why (5 min) -- Decision-making process, not just the decision.
4. Architecture Deep Dive (10 min) -- Go deep on 2-3 components. NOT a tour of every box.
references/whiteboard-diagrams.md)5. Results & Impact (3 min) -- Quantified outcomes.
6. What I Would Change (2 min) -- The most important 2 minutes.
7. Q&A (15+ min) -- Where the real evaluation happens.
The cardinal sin is covering everything at surface level. Pick 2-3 layers to go DEEP.
| Component Type | Skim (1-2 sentences) | Medium (2-3 min) | Deep (5+ min) |
|---|---|---|---|
| Standard infra (load balancer, CDN) | Almost always skim | Only if custom config | Never unless this IS the project |
| Data storage layer | If standard SQL/NoSQL | If sharding, replication, or hybrid | If you designed the storage engine |
| ML model architecture | If off-the-shelf | If fine-tuned or modified | If custom architecture or novel approach |
| Data pipeline | If standard ETL | If real-time or complex transforms | If you solved a hard data quality problem |
| API/interface design | If REST/GraphQL standard | If complex versioning or contracts | If protocol design was the core challenge |
| Monitoring/observability | Usually skim | If anomaly detection is core | If 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.
The Q&A is where interviewers separate builders from bystanders. Prepare for these patterns:
Adjust depth based on who's in the room:
| Audience | Emphasize | De-emphasize |
|---|---|---|
| Researchers / scientists | Novel approaches, evaluation methodology, ablation studies | Infra details, deployment ops |
| Backend / systems engineers | Scale, reliability, performance tradeoffs, failure handling | ML model internals, business context |
| ML engineers | Model architecture, training pipeline, data challenges, serving infra | Business impact, team dynamics |
| Engineering managers | Decision-making process, team coordination, technical risk management | Low-level implementation details |
| Mixed panel | Start broad, let Q&A reveal where each panelist wants depth | Don't pre-optimize for one audience |
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.
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.
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.
| File | Consult When |
|---|---|
references/project-narrative-template.md | Structuring a project presentation from scratch; filling out the narrative arc; preparing Q&A answers; worked example of an ML pipeline presentation |
references/whiteboard-diagrams.md | Planning 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
SKILL.md and 3 other files (references) in .claude/skills/tech-presentation-interview of curiositech/some_claude_skills.
Open the folder on GitHubat commit 6713fc7
Tech Presentation Interview next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Tech Presentation Interview this skillcuriositech/some_claude_skills | 243 | — | ~3.6k | Automated safety check: Pass | MIT | |
| Backend and Agent Project Selectorlishuangqiang/backend-agent-resume-scout | 347 | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| Binary Trees InterviewerPrepLabsAI/InterviewMentor | 112 | — | ~2.4k | Automated safety check: Pass | MIT | |
| Nextjs React ExpertDokhacgiakhoa/Agent-Skills-4-Vibe-Coding-CLI | 507 | — | ~1.7k | Automated safety check: Pass | Custom licence | |
| Deep Analysisnicepkg/auto-company | 192 | 2 repos | ~2.7k | Automated safety check: Notes | None | |
| Make FiguresAperivue/medsci-skills | 329 | — | ~8.4k | Automated safety check: Pass | MIT |
lishuangqiang/backend-agent-resume-scout
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nicepkg/auto-company
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Categories
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.
Tech Presentation Interview fits situations like: project selection; narrative arc structuring; whiteboard diagrams; depth calibration.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.