> For the complete documentation index, see [llms.txt](https://lilo.gitbook.io/lilocookbook/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://lilo.gitbook.io/lilocookbook/start-here.md). # Start Here Open the LiLO Resume Tailoring Project [Click here to start](https://chatgpt.com/g/g-p-690b22ce50d88191b98bf3e9a460697b-resume-rewrites/project) #### Step 1: Upload the Job Description {% code overflow="wrap" %} ```markdown Job Description Analysis Using the context in 'how_to_tailor_your_resume.md' and 'metricdiscoveryprompt.md', extract the following information from the job description below. [Paste the full job description here] Identify and list: Must-have qualifications — essential skills, experiences, or credentials without which a candidate would not be considered. Nice-to-have qualifications — secondary or bonus skills that strengthen a candidate’s fit. Above-and-beyond or standout traits — signals of an exceptional applicant (leadership, impact scale, rare technical depth, etc.). Core responsibilities — what the role is accountable for delivering. Keywords / tools — specific terms or technologies that should be echoed in tailored resume bullets (rank these by importance). Present your findings as a Tailoring Checklist, formatted with checkboxes (☐). Before returning results, confirm that each category reflects LiLO’s definitions of must-have vs. nice-to-have (see context). ``` {% endcode %} *** #### Step 2: Choose the Experience to Tailor Pick 1 project or internship that fits this job: {% code overflow="wrap" %} ```prompt Experience Selection & Rewrite Setup Using the Tailoring Checklist from Step 1 and the context files how_to_rewrite_a_resume.md, metricdiscoveryprompt.md, before_greater_than_after.md, and especially star_xyz_fusion.md, help me select and rewrite one experience for this role. Role Type: (e.g., Backend Intern — Company — Dates) My raw bullets / notes (paste exact text): (Paste exact Bullets Here) - Required Extra context (optional): links/specs, stack, scale, users, latency, data size, $$ impact. Do this in order: Targeting plan: From the Step-1 Checklist, list the top 3–5 items this experience can credibly hit. Quote them verbatim and rank by importance. Gap queries (max 6): Ask only the smallest set of questions needed to surface missing details about scope, scale, tools, and outcomes. Use metricdiscoveryprompt.md for guidance. Rewrite (3–4 bullets):   • Follow the S + T → XYZ method from star_xyz_fusion.md.   • Make sure each bullet:    – Begins with a strong action verb.    – Contains S + T to explain why the work mattered and XYZ to show what you did and what changed.    – Includes a specific tool or system and one truthful metric (time saved, perf gain, users impacted, etc.).    – Maps to at least one Checklist item from Step 1.   • Avoid duplicate sentence shapes and generic phrasing (see how_to_rewrite_a_resume.md). Traceability table: Return a table with columns: Checklist Item Hit | Final Bullet | Proof (Tool/Metric) | Why It Mattered. Integrity check: Flag any metric that’s assumed or estimated as NEEDS CONFIRMATION so I can verify it. After Step 2, pause for my answers (if you asked questions) or my confirmation before continuing. ``` {% endcode %} *** #### Step 3: Fill in the Gaps (Q\&A) * AI will ask you targeted questions. * Be honest and specific. If you don’t have a metric, just describe the result qualitatively. {% code overflow="wrap" %} ```prompt Context Gap Q&A (Be Specific + Truthful) Using the outputs from Step 2 — your targeting plan, ranked checklist items, and the initial draft bullets — ask up to 6 targeted questions to uncover any missing context before rewriting. Ground your questions and later rewrites in these context files: metricdiscoveryprompt.md, star_xyz_fusion.md, and how_to_rewrite_a_resume.md. Question types to prioritize: Scope: team size, number of users affected, data volume, traffic scale, deployment environment. My role: what I personally built, designed, or owned vs. what the team handled. Tools used: specific frameworks, languages, libraries, or versions. Results: quantitative (latency, accuracy, adoption, cost/time savings) or qualitative if numbers are unknown. Constraints: security, accessibility, performance, or reliability considerations. Fabrication Rule: Never invent or infer numbers, tools, or outcomes. If data is missing, create an inline note in square brackets: [TO-DO: clarify X metric] or [TO-DO: add context on reliability improvements]. Use these placeholders only where a fact must later be confirmed. After asking your questions and receiving my answers, regenerate 3–4 bullets following the S + T → XYZ method from star_xyz_fusion.md. Each bullet should include: One verified metric or qualitative descriptor (if no metric). One clear action verb + technical noun. A mapping back to at least one Step-1 checklist item. End your response with a short “Pending TO-DOs” list that summarizes any placeholders needing confirmation. If the role is technical, consult metricdiscovery_swe.md; otherwise consult metricdiscovery_general.md. Ask at most 6 questions total, then summarize metrics as Baseline→After→Δ with timeframe and source; use [TO-DO: …] for any missing confirmations. ``` {% endcode %} *** #### Step 4: Rewrite Your Bullets * Copy the rewrite prompt. * Get your improved bullets in STAR + XYZ format. * Paste the new ones into your resume doc. {% code overflow="wrap" %} ``` Final Resume Bullet Rewrite Using all confirmed context from Steps 1–3 including the JD Tailoring Checklist, targeting plan, and verified Q&A responses rewrite my selected experience into 3–4 polished bullets. Reference the following context files: star_xyz_fusion.md, how_to_rewrite_a_resume.md, and before_greater_than_after.md. Instructions: Follow the S + T → XYZ structure from star_xyz_fusion.md. Keep every statement truthful and verifiable. If any detail is uncertain, insert a clear placeholder in brackets, e.g. [TO-DO: confirm latency impact]. Each bullet must: • Begin with a strong action verb. • Include one technical noun (tool, framework, or system). • Contain one metric or qualitative descriptor showing the result. • Map explicitly to at least one checklist item from Step 1. Use variation in sentence rhythm; avoid repetition of structure or verbs (see how_to_rewrite_a_resume.md). If all context gaps were already filled in Step 3, proceed directly with the rewrite—no further questions needed. Return: Final bullets (3–4 lines). A brief summary of alignment, which checklist items each bullet satisfies. A short “Pending TO-DOs” list, if any placeholders remain. ``` {% endcode %} *** #### Step 5: Quality Check * Run the following checks when needed: #### Context Check *When to use:* If someone who doesn’t know you (like a recruiter) would be confused by reading your bullets, you’ve got work to do. {% code overflow="wrap" %} ```prompt Using the S + T → XYZ method from star_xyz_fusion.md, review these bullets for clarity. If the Situation or Task is unclear, add a single intro line or short clause that explains why the work mattered. Do not change verified facts. [Paste bullets here] ``` {% endcode %} #### Metrics Check *When to use:* if your bullet describes what you did but doesn’t show the impact, scale and result. {% code overflow="wrap" %} ```prompt For each bullet, ensure there is one honest, verifiable measure of impact (time, scale, performance, users, revenue, etc.). If a metric is missing, add a placeholder note in brackets e.g. [TO-DO: measure latency reduction] — and stop. [Paste bullets here] ``` {% endcode %} #### Tighten *When to use:* if your bullets all start to sound the same or rely on buzzwords instead of proof. {% code overflow="wrap" %} ```prompt Tighten these bullets. Remove filler, repeat nouns sparingly, keep one metric per bullet, make verbs concrete. [Paste bullets] ``` {% endcode %}