How to Use

Follow one project through every Intent skill — from first question to engineering handoff.

The project: Nearby — A neighborhood marketplace for buying, selling, and trading within walking distance.

intent

Established project context, user types, design principles, and constraints for a hyperlocal marketplace.

We started by grounding the project in reality. Nearby isn't another e-commerce platform — it's a tool for neighbors. That distinction shapes everything: trust is built through proximity, not star ratings. We defined three core user types, set design principles that prioritize safety and simplicity, and named the constraints that would keep us honest.

strategize

Framed the market opportunity, mapped competitors, defined a testable hypothesis, and scoped the MVP.

We stepped back to ask whether this idea has legs. The hyperlocal exchange space is littered with failures — Yerdle, OfferUp's local push, Facebook Marketplace's neighborhood tab. Each solved the wrong problem. We mapped what they got wrong, sized the opportunity differently (not by GMV but by exchange density per square mile), and wrote a hypothesis we could actually test.

/philosopher

What does "neighborhood" actually mean? In a dense urban block, walking distance might be 0.2 miles — you can see the seller's building from your window. In a suburban subdivision, it's the development itself, maybe a mile across. In a rural town, it might be the whole town. The product assumes a shared definition of "nearby" that doesn't exist. Are we building for a radius, a census tract, a zip code, or a felt sense of community? The answer changes the entire trust model.

/storytelling

S/C/R framing isn't decoration. The discipline is: validate the complication against evidence before composing the brief — not after. If the complication can't survive that check, the resolution it implies probably can't either. The first draft of Nearby's complication was sized to fit a "compete with Marketplace" resolution. It didn't survive scrutiny, and the resolution wouldn't have either.

investigate

Designed a research plan with interview scripts for buyers, sellers, and community organizers.

Before designing anything, we needed to hear from people who already do this — the ones selling furniture on their stoop, the buy-nothing group admins managing chaos in Facebook comments, the people who walk past "FREE" signs and wonder what they're missing. We wrote three interview scripts, each tuned to a different relationship with local exchange.

blueprint

Mapped the full service blueprint — actors, frontstage actions, backstage processes, and critical dependencies.

We mapped the invisible machinery behind a simple exchange. What looks like "I want that, here's $5" actually involves geolocation, notification timing, trust inference, content moderation, and a handoff that happens on a physical sidewalk with no platform involvement. The blueprint revealed three critical failure points we hadn't considered.

/storytelling

A blueprint without choreography is an org chart. The temptation here was to draw a clean handoff: buyer → frontend → backend → seller. But the real Nearby service is choreographed across actors who don't yet know each other — the buyer, the seller, the neighborhood density that makes any exchange viable, the moderator catching abuse before it escalates, the future buyers whose trust depends on this exchange working out. Each enters and exits at different moments. Story emerges from the coordination itself, not from any one character's path. Where the blueprint started flattening "the seller" into a system role, we re-introduced who the sellers actually are at each step — a moving-week panicked Sarah, a buy-nothing organizer juggling fifteen DMs — so the team could feel the choreography across real human moments.

journey

Designed four core flows — posting an item, discovering nearby listings, buying, and messaging.

We traced the four paths people actually take through Nearby. Each flow was designed to feel lighter than existing alternatives — fewer taps to post, less scrolling to find, less negotiation to buy. The key insight: in a walking-distance marketplace, the transaction is almost an afterthought. Discovery and coordination are the real product.

/philosopher

The buy/sell mental model assumes every exchange has a price. But in real neighborhoods, the most common local exchange isn't commerce — it's generosity. A bag of lemons from someone's tree. A kid's bike they outgrew. Moving boxes you'll never use again. If Nearby only supports buying and selling, it misses the gift economy that actually builds neighborhood trust. Should "Free" be a price option, or should gifting be an entirely separate mode with different social mechanics?

/storytelling

The protagonist-arc pattern keeps the journey work honest about whose experience we're designing. Sarah moved into the neighborhood three weeks ago, has a couch she needs gone before her parents visit Saturday, and is opening Nearby on her phone in a hallway with bad reception while moving boxes pile up around her. That's the protagonist, the goal, the time pressure. The arc isn't "user posts → buyer arrives → transaction completes." It's the felt experience of hoping someone in her building will save her from a Goodwill run. But there are also Sarahs who are excited, Sarahs who are anxious, Sarahs who aren't moving at all but have a kid's bike that needs a new home. We mapped them as separate arcs rather than smoothing them into one composite — false coherence would hide the real variance from the team.

organize

Defined information architecture — categories, navigation structure, search strategy, and wayfinding.

We organized Nearby around a simple principle: proximity first, category second. Unlike Amazon or even Craigslist, nobody comes to Nearby looking for a specific item. They come to see what's around. The IA reflects browsing behavior, not shopping behavior — the map is the primary navigation, categories are filters, and search is a secondary path.

articulate

Established voice and tone, wrote microcopy for empty states, errors, and trust signals.

We defined how Nearby speaks. The voice is casual, warm, and neighborhood-specific — it should feel like a note on a bulletin board, not a corporate app notification. We wrote copy for the moments that matter most: when nothing's there yet, when something goes wrong, and when someone needs to trust a stranger enough to walk to their house.

evaluate

Ran heuristic evaluation scoring 8 categories, identified 12 issues across severity levels.

We put the emerging design through a structured evaluation before anyone built anything. Scoring across eight UX heuristics revealed strong fundamentals in simplicity and learnability, but exposed gaps in feedback visibility, error prevention, and the trust model's cold-start vulnerability. Twelve specific issues were logged, categorized, and routed to the skills that own them.

fortify

Identified and designed for 9 edge cases — ghost sellers, misrepresentation, cold starts, and abuse scenarios.

We stress-tested the design against real-world human behavior. People ghost. People misrepresent items. People use platforms to harass neighbors. Neighborhoods start with zero content. We designed for each of these — not with heavy-handed moderation, but with lightweight friction that makes bad behavior harder and good behavior easier.

include

Audited accessibility across screen reader, keyboard, cognitive load, and motor access dimensions.

We confronted the hard truth that a map-first interface inherently excludes people who can't see maps. Rather than treating accessibility as a compliance layer, we redesigned the core experience to work across modalities — the list view isn't a secondary mode, it's an equal citizen. We also addressed cognitive load, motor access, and the specific challenges of a location-based app for people with disabilities.

transpose

Analyzed mobile-first vs. web experience, designed for offline scenarios and cross-device continuity.

We designed Nearby for the reality that most exchanges happen on phones, on the move — someone walking past a "FREE" sign, someone browsing while sitting on their porch. But we also designed for the laptop-at-kitchen-table moment: batch-posting after a decluttering weekend, or browsing casually on a bigger screen. And we confronted the offline problem head-on, because not every sidewalk has signal.

localize

Mapped cultural adaptation needs for trust signals, payment norms, content, and RTL support.

We examined what happens when Nearby crosses cultural boundaries. A hyperlocal marketplace is deeply embedded in local norms — how people negotiate, how they build trust, what they're comfortable exchanging with strangers, and what "neighbor" even means. We mapped the changes needed for five distinct cultural contexts and surfaced the assumptions baked into the current design.

/philosopher

Does the Western marketplace model — individual sellers, posted prices, bilateral exchange — translate across cultures? In many communities, exchange is communal, not transactional. Things circulate through extended family networks, religious institutions, or community centers without ever being "listed." The bazaar model assumes negotiation. The gift economy model assumes reciprocity over time, not transaction by transaction. By building a marketplace app, are we importing a cultural frame that only fits some of our users? What would Nearby look like if it were designed for circular exchange rather than linear transactions?

measure

Defined success metrics focused on community health and trust density, not just transaction volume.

We rejected GMV as a north star. For Nearby, gross merchandise value is meaningless — a neighborhood where everyone gives things away for free is a more successful neighborhood than one where everyone haggles. Instead, we designed a measurement framework around exchange density, trust formation, and community health, with explicit counter-metrics to catch growth patterns that harm the product.

specify

Produced engineering handoff specs for the item card component, interest flow, and walking radius algorithm.

We translated design decisions into engineering-ready specifications. Every component got exact measurements, state definitions, interaction details, and API contract requirements. The walking radius algorithm — the core product differentiator — got its own specification with inputs, fallback logic, and performance requirements.

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This is what Intent does for every project. Sixteen skills, six agents, one cohesive design practice.

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