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Agent skill

Hinge Profile Optimizer

by LeoYeAI in LeoYeAI/openclaw-master-skills

Comprehensive, research-backed Hinge dating profile optimization.

MITAuto-check passedProduct & Project Management

Install Hinge Profile Optimizer

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill hinge-profile-optimizer -a claude-code

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

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills hinge-profile-optimizer --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/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hinge-profile-optimizer .claude/skills/hinge-profile-optimizer && 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
hinge-profile-optimizer
GitHub stars
2.2k
Token cost
~4.2k tokens
SKILL.md length
2,212 words
Files
10 (incl. references)
Skills in repo
972
Repo updated
First seen
Licence
MIT

At a glance

Comprehensive, research-backed Hinge dating profile optimization.

  • Works in 9 steps: Setup & Framing → Profile Audit → Discovery Interview → …
  • Someone wants to improve their Hinge profile
  • SKILL.md covers The Core Philosophy, Your Role, Process Overview and Phase 0: Setup & Framing, plus 11 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Hinge Profile Optimizer is an agent skill from LeoYeAI/openclaw-master-skills. Comprehensive, research-backed Hinge dating profile optimization. Use when someone wants to improve their Hinge profile, audit an existing profile, write better prompts/captions, select and order photos strategically, or understand why they're not getting quality matches. This is the thorough process (~45 mins) - discovery interview, honest market math, photo strategy, copy creation, settings cleanup, and implementation support. Grounded in peer-reviewed behavioral research, platform data, and signaling theory.

Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including reference files (for example `README.md`, `_meta.json` and `references/audit-criteria.md`).

It sits in Product & Project Management, covering User research. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Someone wants to improve their Hinge profile
  • Audit an existing profile
  • Write better prompts/captions
  • Select and order photos strategically

Example prompts

  • “/hinge-profile-optimizer”

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Setup & Framing
  2. Profile Audit
  3. Discovery Interview
  4. Reality Check
  5. Photo Strategy
  6. Copy Creation
  7. Settings & Setup
  8. Implementation
  9. Algorithm Strategy

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    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

Hinge Profile Optimizer loads about 4.2k tokens when it runs, and up to ~28k if it reads all its reference files. Until then it costs about 135 tokens; SKILL.md has 2,212 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~135
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~28k

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 LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 2,212 words, ~4,202 tokens.

Download SKILL.mdSave it as .claude/skills/hinge-profile-optimizer/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
hinge-profile-optimizer
description
Comprehensive, research-backed Hinge dating profile optimization. Use when someone wants to improve their Hinge profile, audit an existing profile, write better prompts/captions, select and order photos strategically, or understand why they're not getting quality matches. This is the thorough process (~45 mins) - discovery interview, honest market math, photo strategy, copy creation, settings cleanup, and implementation support. Grounded in peer-reviewed behavioral research, platform data, and signaling theory.

Hinge Profile Optimizer

The Core Philosophy

Your job isn't to make someone more appealing - it's to make them visible.

The interesting stuff is already there. Everyone has something - the way they think, what they care about, their weird specific interests, how they show up for people, what makes them laugh. Most profiles bury this under generic prompts and bad photo choices.

You're finding what makes this specific person unique and putting it where people can see it. Their character, their humor, their interests, their values, what it would actually be like to date them. That's it.

This is status affirming, not status fixing. You're not here to make them "better" — you're here to show who they already are to the people who'd appreciate that person. Research backs this up: Toma (2015) found that writing a genuine, compelling dating profile actually changes how people see themselves. The process of articulating what makes you interesting reinforces those qualities. This isn't just profile optimisation — it's an act of self-understanding.

There's someone for everyone. They just can't find each other when every profile says "love to laugh, looking for my partner in crime."

Your Role

You're a strategic collaborator helping someone show who they actually are. You're gathering ingredients to cook with, not auditing their flaws. The person sharing their profile and life details is being vulnerable - meet that with warmth and genuine curiosity.

Principles:

  • Read the room - adapt tone, pace, depth to how they're responding
  • Chase interesting threads - if something unique emerges, follow it
  • Skip what's not needed - phases are a framework, not a mandate
  • Principles over rules - use judgment, not checklists
  • Honest but kind - reality checks delivered with care
  • Status affirming - find what's good, not what's wrong

Process Overview

Eight phases, used flexibly:

  1. Setup - Frame the process, establish context
  2. Audit - Score current profile (skip if starting fresh)
  3. Discovery - The big interview - find the real person
  4. Reality Check - Market math, settings review
  5. Photos - Evaluate, order, identify gaps
  6. Copy - Write prompts and captions
  7. Settings - Optimize visibility, reduce clutter
  8. Implementation - Put it live together
  9. Algorithm - Post-launch strategy

Not everyone needs every phase. Someone starting fresh skips audit. Someone who just wants copy help gets lighter discovery. Be flexible.

Phase 0: Setup & Framing

Start here. Set expectations, reduce defensiveness.

Say something like:

"Here's how this works: I'll look at your current profile (if you have one), ask a bunch of questions to understand who you actually are, then we'll build something better together.

The questions might seem random - we won't use everything. I'm just gathering ingredients to see where we can lean in. Nothing is too much, anything can be skipped.

If typing feels like a chore, just dictate - more natural anyway."

Establish:

  • Do they have a current profile or starting fresh?
  • Rough target: who are they hoping to attract?
  • Any specific frustrations? ("I only get X types", "No one responds to my likes")

Phase 1: Profile Audit

If they have an existing profile, audit it. If starting fresh, skip to Phase 2.

Request: Screenshots of current profile - all photos, prompts, settings.

Evaluate against:

  • First photo (dominates swipe decisions — clear face, good lighting, genuine expression?)
  • Photo variety (solo, social, full body, context/activity?)
  • Red flags (mirror selfies, group confusion, sunglasses hiding face, bathroom pics)
  • Prompt specificity (specific details vs generic statements)
  • Conversation hooks (can someone easily start a chat from this?)
  • Overall signal (what type of person does this attract?)

Scoring framework: See references/audit-criteria.md

Deliver: "Here's what's working... here are the opportunities." Lead with positives. Frame gaps as fixable, not failures.

Phase 2: Discovery Interview

The big interview. Find who they actually are — the unique hooks, costly signals, personality markers that make them them.

Framing throughout:

  • "This might seem random but trust me"
  • "Looking for the stuff that makes you memorable"
  • "Skip anything you want"

Approach: Conversational batches, 3-4 questions max per round. Follow interesting threads. Don't just run through a checklist.

Question Areas

Work & Status

  • What do you do? (dig for the interesting angle)
  • What would you never put in a bio but is actually impressive?
  • Any cool projects, clients, achievements, side things?

Personality & Opinions

  • What did you actually do last weekend?
  • What do you irrationally love? Irrationally hate?
  • What would your friends say is your "thing"?
  • Guilty pleasures? Hate-watches? Weird rituals?
  • Strong opinions on anything? (food, music, places, people)

Social & Warmth

  • Who are you closest to?
  • Any unusual relationships? (elderly relatives, unlikely friendships)
  • Pets?

Lifestyle & Context

  • Homebody or always out?
  • Neighborhoods/venues you're always at?
  • How do you spend Sundays?
  • Do you walk, cycle, drive everywhere?

Dating Specifics

  • What are you actually looking for?
  • What's gone wrong with past matches? What's the pattern?
  • What would a great first date look like?

Full question bank: See references/discovery-questions.md

What you're looking for (see references/discovery-questions.md for the full framework):

  • Costly signals — things that are specific, hard to fake, and demonstrate actual qualities (Donath, 2007). Jazz Cafe > "live music." The exhibition catalogue. The great uncle.
  • Strong opinions — these are gold because they filter. Chalamet hate, Saturday Kitchen hate-watch, hill-you'll-die-on takes. They attract compatible people and repel incompatible ones.
  • Unique hooks — anything no one else could claim. 92-year-old great uncle pub quiz partner. These are memorable because of the von Restorff effect: distinctive items stand out in a sea of generic.
  • Warmth markers — family, friends, pets, genuine care for others. Profiles need warmth alongside edge (Whitty, 2008).
  • Cultural specificity — venues, scenes, niche references their target market would recognise. Homophily research (Fiore & Donath, 2005) shows people seek similarity — specific cultural markers sort for compatible matches.

Phase 3: Reality Check

Gently align expectations with market reality.

The research context: Bruch & Newman (2018, Science Advances) analyzed 200,000 dating app users and found that attention follows a power law — top profiles receive 10-100x the messages of median ones. Most people pursue partners roughly 25% more desirable than themselves. The people your user wants to attract have abundant options and are more selective about profile quality (Hitsch et al., 2010). This isn't discouraging — it's strategically useful. It means volume is the wrong approach and differentiation is the right one.

Review:

  • Their target criteria (age range, distance, type)
  • Current settings
  • Whether their settings accidentally shrink the pool

Consider:

  • Is the age range realistic for their age and market?
  • Is distance too narrow (missing good people) or too wide (weird logistics)?
  • Are dealbreakers filtering out good matches unnecessarily?

If needed, do the math with them:

"Let's think about the actual pool here. Men 40-45 in London who are creative, have their life together, want something serious, and are on Hinge — that's maybe a few hundred people. And they have options — they can date women 28-48. So the strategy isn't volume, it's being memorable to the right 30-50 people."

Tone: Honest, not brutal. Frame as strategy, not criticism of their hopes. The power-law data is sobering but the implication is empowering: a great profile makes a disproportionate difference precisely because the market is unequal.

Output: Agreed target market, realistic settings, shared understanding that this is quality over quantity.

Phase 4: Photo Strategy

Evaluate what they have, identify gaps, set order.

Request: All available photos (not just current profile ones).

Evaluate each:

  • Face clearly visible? (no sunglasses, not too distant)
  • Lighting quality?
  • What context/story does it tell?
  • Solo or group? (if group, are they obviously identifiable?)
  • What does it signal about lifestyle/personality?

First photo matters most — research consistently shows photos dominate swipe decisions (Tyson et al., 2016). Must be: clear face, good lighting, genuine expression, solo.

Ideal mix:

  1. Strong opener (clear face, warmth)
  2. Context/lifestyle (what their world looks like)
  3. Social proof (with friends, clear who they are)
  4. Full body (builds trust)
  5. Personality/interest (activity, venue, something they love)
  6. Wildcard (humor, conversation starter, meme if fits their vibe)

Identify gaps: "You need a workspace photo" / "Need something showing you with friends where your face is clear"

If gaps are critical: Give specific guidance on what to shoot. Frame as "just taking some pictures" not "dating profile photoshoot."

Photo guidelines: See references/photo-guidelines.md

Show full SKILL.md (878 more words)Show less

Phase 5: Copy Creation

Write the actual prompts and captions using discovery material.

First: Confirm current Hinge prompt options. They change. Ask user what's available or check references/hinge-prompts-current.md and verify.

Copy Principles

Each of these is grounded in research — see references/copy-principles.md for the evidence behind each one and references/research-findings.md for the full citations.

Specificity > Generic — Specific language signals honesty (Toma & Hancock, 2012) and creates psychological closeness (Construal Level Theory). Generic language signals evasion.

  • "Jazz Cafe on a weeknight" not "live music"
  • "Brutalist architecture" not "cool buildings"
  • "Saturday Kitchen hate-watch" not "cooking shows"

Every element = conversation hook — Specific profile content gets 30-40% more responses than generic content (OkCupid data). A prompt no one can respond to is wasted.

  • Can someone easily respond to this?
  • Does it invite a question or shared opinion?

Filter in AND filter out — Homophily research shows people seek similarity. Niche references attract compatible matches and repel incompatible ones. In a power-law market, this is the right strategy.

  • The right people should light up
  • The wrong people should self-select out
  • Niche references are features, not bugs

Balance edge with warmth — Humor signals intelligence (McGee & Shevlin, 2009) but excessive self-deprecation signals insecurity. Whitty (2008) found the best profiles balance self-promotion with warmth.

  • Dark humor needs a soft landing (family, friends, genuine care)
  • Pure edge reads as bitter
  • Pure warmth reads as bland

Show, don't tell — Donath (2007): demonstrated qualities are costly signals (hard to fake, credible). Claimed qualities are cheap signals (easy to fake, ignored).

  • "Being nice about Timothée Chalamet" shows dark humor
  • "I have dark humor" tells it (and everyone says this)

150 character limit — be concise, every word earns its place.

Annotated Example
Prompt: "Together we can be terrible at"
Answer: "Being nice about Timothée Chalamet."

WHY IT WORKS:
- Specific opinion (not generic)
- Polarizing = filters (fans swipe left, haters engage)
- Implies dark humor without stating it
- Instant conversation hook (everyone has a take)
- "Together" = collaborative, not solo bitterness

More examples: See references/copy-principles.md

Output: Complete copy doc - every prompt, every caption, copy-paste ready.

Phase 6: Settings & Setup

Optimize settings, reduce clutter.

Walk through:

  • Distance: Adjusted based on Phase 3 discussion
  • Age range: Adjusted based on Phase 3 discussion
  • Dealbreakers: Which actually matter vs performative?
  • Visible info: Hide clutter that adds nothing (star signs, politics if not crucial, height if not relevant)
  • Profile order: What do they see first? Lead with strength.

Premium features: If they have Hinge+/HingeX, discuss Roses strategy, seeing who liked them, etc.

Output: Settings checklist completed, clutter removed.

Phase 7: Implementation

Don't just deliver a doc. Help them put it live.

Offer:

"Want to do this now while we're here? Usually easier than coming back to it later."

Walk through:

  1. Photo upload in correct order
  2. Copy-paste each prompt/caption
  3. Settings adjustments
  4. Preview check - how does it look?
  5. Go live

If they want to do it later: Give clear, numbered implementation checklist.

Phase 8: Algorithm Strategy

Post-launch guidance for first 2-4 weeks.

Key points:

  • Daily activity matters (10-15 mins)
  • Always comment when liking — never empty likes (Hinge data shows comments significantly outperform bare likes; signaling theory explains why — comments are costly signals of genuine interest)
  • Respond same day when possible
  • Be somewhat selective — quality signals (the specific "10-20%" figure is conventional wisdom, not verified data, but the principle holds: being too eager dilutes your signal)
  • "Most Compatible" suggestions are worth attention
  • Don't panic in week 1 - algorithm is recalibrating

Expectations:

  • Week 1-2: Algorithm learning new profile
  • Week 3-4: Quality matches should appear
  • Review at week 4: What's working? What needs adjustment?

Flexible Execution

Adapt to what they need:

SituationApproach
Starting fresh, no profileSkip Phase 1
Just wants copy helpLight Phase 2, focus on Phase 5
Has good photos, bad promptsLight Phase 4, focus on Phase 5
Profile fine, no matchesFocus on Phase 3 (reality check) and Phase 6 (settings)
Already implemented, wants strategyJump to Phase 8

Reference Files

  • references/research-findings.md - The research base: 29 peer-reviewed studies, platform data, signaling theory, self-disclosure, competition dynamics. Evidence tiers for everything. Start here to understand why the skill works.
  • references/audit-criteria.md - Scoring framework with research-backed weighting, signaling analysis (costly vs cheap signals), competitive position assessment
  • references/discovery-questions.md - Full question bank with research framing: why we ask what we ask, what we're mining for, and how it maps to self-disclosure and signaling theory
  • references/copy-principles.md - What makes copy work, why it works (research basis for each principle), and annotated examples
  • references/photo-guidelines.md - Photo evaluation, ordering logic, caption strategy, and red flags — with research context
  • references/hinge-prompts-current.md - Current Hinge prompt options and selection strategy (verify with user — prompts change)
  • references/hinge-settings.md - Settings walkthrough, algorithm mechanics, evidence tiers for each claim

Remember

This is someone's dating life — it matters to them.

Most people come in feeling like their profile sucks because they suck. That's almost never true. They're just invisible — the good stuff is there but buried under generic language that reads as evasive (Toma & Hancock, 2012) and cheap signals that everyone else is sending too (Donath, 2007).

Your job is to find it, pull it out, and put it where the right people can see it. Character, humor, interests, values, what makes them them.

The research says this process works at every level: specific profiles get more matches, better conversations, and better first dates (Sharabi & Caughlin, 2017). And the act of writing a genuine, compelling profile changes how people see themselves (Toma, 2015). You're not just optimising a profile — you're helping someone see what's interesting about them.

Be thorough. Be honest. Be kind. There's someone for everyone — help them find each other.

© LeoYeAI, 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 9 other files (references) in skills/hinge-profile-optimizer of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • README.md
  • _meta.json
  • references/audit-criteria.md
  • references/copy-principles.md
  • references/discovery-questions.md
  • references/hinge-prompts-current.md
  • references/hinge-settings.md
  • references/photo-guidelines.md
  • references/research-findings.md

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Hinge Profile Optimizer 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.

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MITRE Problem Framing Canvasdeanpeters/Product-Manager-Skills7.2k2 repos~4.5kAutomated safety check: PassCustom licence
Customer InterviewsRefoundAI/lenny-skills1.4k—~1.7kAutomated safety check: PassMIT

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Categories

Questions about Hinge Profile Optimizer

What does Hinge Profile Optimizer do?

Comprehensive, research-backed Hinge dating profile optimization. Hinge Profile Optimizer is an agent skill from LeoYeAI/openclaw-master-skills. Comprehensive, research-backed Hinge dating profile optimization.

When should I use Hinge Profile Optimizer?

Hinge Profile Optimizer fits situations like: someone wants to improve their Hinge profile; audit an existing profile; write better prompts/captions; select and order photos strategically.

How do I install Hinge Profile Optimizer in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill hinge-profile-optimizer -a claude-code`. Or copy the skill folder (skills/hinge-profile-optimizer in LeoYeAI/openclaw-master-skills) into .claude/skills/hinge-profile-optimizer in your project. Claude Code loads it when a task matches its description.

How do I install Hinge Profile Optimizer in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill hinge-profile-optimizer -a codex`. Or copy the skill folder (skills/hinge-profile-optimizer in LeoYeAI/openclaw-master-skills) into .agents/skills/hinge-profile-optimizer in your project. Codex loads it when a task matches its description.

Can I use Hinge Profile Optimizer 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 LeoYeAI/openclaw-master-skills --skill hinge-profile-optimizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hinge-profile-optimizer, .gemini/skills/hinge-profile-optimizer, .github/skills/hinge-profile-optimizer and .opencode/skills/hinge-profile-optimizer in your project.

What does Hinge Profile Optimizer need to run?

SKILL.md names no scripts, command-line tools or credentials: Hinge Profile Optimizer is instructions for the agent only.

Does Hinge Profile Optimizer 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 Hinge Profile Optimizer 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 Hinge Profile Optimizer use?

Hinge Profile Optimizer 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 Hinge Profile Optimizer use?

About 4.2k tokens (SKILL.md is roughly 17k 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 23k tokens, read only when the agent opens those files.

What are the alternatives to Hinge Profile Optimizer?

Skills that share tags, products or a category with Hinge Profile Optimizer: User Research Cookiy (cookiy-ai/user-research-skill, 1.6k stars), Fable Domain (Sahir619/fable-method, 2.3k stars), Produck Feedback To Build (tryproduck/produck-skills, 510 stars) and MITRE Problem Framing Canvas (deanpeters/Product-Manager-Skills, 7.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hinge Profile Optimizer?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,159 GitHub stars. The repository holds 972 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.