Common App-AI university essay builder

Example

Input: a jumble of experiences (course projects, hackathon, internship). Output: a tight outline using the four-part structure—Motivation hook; Background evidence (2–3 strongest experiences with Context–Action–Result); Bridge to goals (what your recent work prepared you to do next); Future plan with program/faculty alignment. The outline auto-allocates word count (e.g., 15% intro, 55% evidence, 15% bridge, 15% future) and includes sentence starters to avoid throat-clearing.

Scenario

Applicant to an MS in Robotics needs a 1000-word SOP. Common App extracts two projects (gesture-controlled arm; SLAM mini-project), quantifies results (reduced drift by 37% after sensor fusion), then assigns paragraph roles: Paragraph 1—problem-driven hook; Paragraphs 2–3—evidence mini-stories with numbers; Paragraph 4—why grad school now; Paragraph 5—faculty-aligned plan. The result reads cohesive and intentional rather than a chronological résumé dump.

Example

Transforms soft claims into verifiable impact using CAR/PAR frameworks (Context–Action–Result / Problem–Action–Result). Weak: “I learned leadership as club president.” Strong: “Faced 42% member attrition, I rebuilt onboarding with peer-led micro-labs; attendance rose from 11 to 29 per session, and project completion doubled in one semester.” It also trims hedging, replaces passive voice, and adds crisp verbs.

Scenario

For a 250-word ‘community contribution’ supplement, Common App asks: What exact problem? What constraint? What metric moved? It prompts for before/after numbers, stakeholders, and a one-line insight (“Make it easy to start; excellence follows”). You receive a 3–5 sentence vignette with a memorable pivot, then a 1–2 sentence reflection that ties the story to the program’s values—clear impact without fluff.

Example

Generates tailored ‘Why this program’ and ‘Future work’ blocks by turning your interests into 2–3 concrete research themes and corresponding questions. It provides a template to reference faculty/labs authentically (what they work on, why it matters to your trajectory, and the collaboration angle) and prompts you to avoid name-dropping without substance.

Scenario

A Data Science applicant focusing on causal inference wants a 180-word school-specific paragraph. Common App helps articulate: Theme—policy evaluation under shifting confounders; Question—robust identification in high-dimensional settings; Application—public health resource allocation. It then drafts a paragraph structure: 1) one-sentence program hook (methods + domain), 2) two-sentence faculty/lab synergy statement (methods overlap + how you’d extend), 3) one-sentence outcome vision (tooling you’ll build and who benefits). You swap in the exact faculty once you confirm them, keeping the paragraph precise and honest.