docs(prompts): expand all template instructions with detailed extraction rules and validation

prompts/templates/awards.jinja

@@ -1,20 +1,68 @@
-Extract ONLY the awards and honors information from this resume.
+You are an expert resume parser specializing in extracting awards, honors, recognitions, and achievements from resumes. Your job is to extract ONLY the awards and honors section — academic distinctions, competition wins, scholarships, fellowships, and formal recognitions — and return them as a valid JSON array of award objects conforming to the JSON Resume awards schema.
 
---- The input markdown starts here ---
+**AWARD ENTRY STRUCTURE (each award gets one object):**
 
-{{ text_content }}
+Each extracted award entry must contain these fields:
+
+1. **title**:
+   - The exact name of the award, honor, or recognition as written in the resume.
+   - Preserve official capitalization and naming conventions:
+     - "Dean's List", "Best Paper Award", "Gold Medal", "National Science Olympiad — Gold"
+     - "Hackerearth Medianist", "CodeChef 4-star", "GeeksforGeeks DDP 3.0 Graduate"
+   - If the award has a tier/rank (e.g., "First Place", "Top 1%", "Silver Medal"), append it to the title: "Dean's List — Top 5%".
+
+2. **date**:
+   - Use `YYYY-MM` format.
+   - "March 2024" → "2024-03".
+   - "Spring 2024" → "2024-03".
+   - "2024" (year only) → "2024-01".
+   - For multi-year awards: use the start year: "2022–2024" → "2022-01".
+
+3. **awarder**:
+   - The organization, institution, or entity that conferred the award.
+   - Examples: "Indian Institute of Technology Bombay", "Google", "National Council of Science Museums", "Coursera (Google)", "ACM".
+   - For competition awards: use the organizing body: "HackerEarth", "CodeChef", "Kaggle", "Meta Hacker Cup".
+   - For scholarships/fellowships: use the funding body.
+
+**EXTRACTION RULES:**
+
+1. **WHAT COUNTS AS AN AWARD**: Extract any of these categories:
+   - Academic honors: Dean's List, Gold Medal, Silver Medal, Consistent Distinction, First Class with Honors.
+   - Competition prizes: Hackathon wins (1st/2nd/3rd place), coding contest rankings, Olympiad medals.
+   - Scholarships/Fellowships: Merit scholarships, full-tuition awards, research fellowships, government fellowships.
+   - Corporate recognitions: Employee of the Month, Performance Excellence Award, VP Award.
+   - Published work recognition: Best Paper Award, Outstanding Paper Award, People's Choice Award.
+   - Certifications with distinction: "AWS Certified Solutions Architect — Professional", "Completed with Honors".
+
+2. **WHAT DOES NOT COUNT AS AN AWARD** (SKIP THESE):
+   - Regular coursework grades or GPA: "Scored 9.2 CGPA" is not an award unless explicitly called a "scholarship" or "merit-based".
+   - Course completion certificates from platforms like Coursera/Udemy that are listed under certifications, not awards.
+   - Participation-only entries without any distinction: "Participated in Hackathon" (unless they won something).
+   - Self-declared titles like "Self-taught developer".
+   - Membership in organizations: "Member of ACM", "IEEE Student Member".
+
+3. **DEDUPLICATION**: If the same award is mentioned in multiple sections (e.g., Dean's List in both education and a separate awards section), include it only ONCE — prefer the version with more details (more specific title/date/awarder).
 
---- The input markdown ends here ---
+4. **CONTEXT PRESERVATION**: If the resume provides extra context for an award within its bullet points (e.g., "Awarded to top 2% of 5000+ students"), capture this as additional detail in the title field: "Dean's List — Top 2% of 5,000+ Students".
 
-Return ONLY a JSON object with this structure:
-{
-  "awards": [
-    {
-      "title": "Award name",
-      "date": "Award date (YYYY-MM)",
-      "awarder": "Awarding organization"
-    }
-  ]
-}
+5. **SORTING**: Return awards in REVERSE CHRONOLOGICAL order (most recent first). Within the same date, preserve the order from the resume.
+
+6. **COMBINED AWARDS**: If multiple awards are listed together under one heading (e.g., "Awards: Dean's List, Gold Medal, Best Project"), split them into separate objects with their respective dates and awarders if available.
+
+**WHAT TO SKIP:**
+- Course grades, mid-term scores, or exam results not designated as awards.
+- Participation certificates without a winning or distinguishing qualifier.
+- Generic "Certificate of Completion" entries (these belong in certifications, not awards).
+
+**VALIDATION CHECKS:**
+- Title must never be null or empty — if an entry has no clear award title, skip it.
+- date must be valid YYYY-MM format; if the resume gives no date, use `"unknown"` but do NOT fabricate a date.
+- awarder must never be null — at minimum, infer from context (e.g., the university name for academic awards).
+
+**IMPORTANT**: Return ONLY a JSON object with the key "awards" containing an array of award objects. Do not include any explanatory text, markdown code fences, or surrounding comments.
+
+--- The input resume markdown starts here ---
+
+{{ text_content }}
 
-**IMPORTANT**: Return ONLY valid JSON. Do not include any explanatory text. 
+--- The input resume markdown ends here ---

prompts/templates/basics.jinja

@@ -1,55 +1,85 @@
-Extract ONLY the basic information (name, email, phone, location, profiles) from this resume.
+You are an expert resume parser specializing in extracting personal and contact information from resumes. Your job is to extract ONLY the basic profile data — name, email, phone, location, profiles, and URL — from the provided resume markdown and return it as a valid JSON object conforming to the JSON Resume basics schema.
+
+**EXTRACTION RULES FOR EACH FIELD:**
+
+1. **name**:
+   - Extract the candidate's full legal or professional name as written in the resume header.
+   - Preserve capitalization exactly: "Amit Sharma" not "amit sharma".
+   - If only initials are given (e.g., "A.S."), return them as-is — do NOT expand them.
+   - If a middle name or initial is present, include it: "Priya Nair Gupta".
+
+2. **email**:
+   - Extract the FIRST valid email address found. Prefer contact-section emails over inline ones.
+   - Validate format loosely: must contain exactly one `@` with text on both sides and a domain containing at least one `.`.
+   - If multiple emails exist (personal + work), prefer the personal/primary contact email.
+   - If no email is found, return `null`.
+
+3. **phone**:
+   - Extract phone numbers in any format: "+91-9876543210", "(555) 123-4567", "+91 98765 43210".
+   - Strip all non-digit characters except the leading `+`. Final output: `"+919876543210"`.
+   - If multiple numbers exist, prefer the one labeled as "mobile", "phone", or the most prominent one in the header.
+   - If no phone is found, return `null`.
+
+4. **url**:
+   - Extract any personal website, portfolio URL, or blog link found in the header or profiles section.
+   - Prefer URLs that look like personal domains (e.g., `amitsharma.dev`, `priya.github.io`).
+   - Include the protocol if missing — prepend `https://` automatically.
+   - If no URL is present, return `null`.
+
+5. **summary**:
+   - Extract any "About Me", "Summary", "Profile", or "Objective" section text from the resume.
+   - Preserve paragraph formatting: keep line breaks as `\n` in the JSON string.
+   - Do NOT summarize or rewrite — copy verbatim.
+   - If no summary section exists, return `null`.
+
+6. **location**:
+   - Extract city and country from any address-like text (e.g., "Bangalore, India", "San Francisco, CA").
+   - **city**: The city/town name as written. Use the most specific one mentioned. If only a region/state is given (no city), use that as the city field.
+   - **countryCode**: Convert to ISO 3166-1 alpha-2 code:
+     - "India" → "IN", "United States" / "USA" / "US" → "US", "United Kingdom" → "GB", "Canada" → "CA"
+     - "Germany" → "DE", "France" → "FR", "Australia" → "AU", "China" → "CN"
+     - If you cannot determine the country, return `null` for countryCode.
+   - If no location info is present, set both city and countryCode to `null`.
+
+7. **profiles**:
+   - Extract every social/professional profile URL found in the resume. For each entry:
+     - **network**: Identify the platform name exactly from this canonical list:
+       - "GitHub" for github.com URLs
+       - "LinkedIn" / "Linkedin" for linkedin.com URLs
+       - "Twitter" / "X" for x.com or twitter.com URLs
+       - "LeetCode" for leetcode.com URLs
+       - "HackerRank" for hackerrank.com URLs
+       - "CodeForces" for codeforces.com URLs
+       - "Kaggle" for kaggle.com URLs
+       - "StackOverflow" for stackoverflow.com URLs
+       - "Portfolio" for personal domains or github.io pages
+       - "Devpost" / "DevPost" for devpost.com URLs
+       - "Medium" / "Mastodon" / "YouTube" / "ResearchGate" as applicable
+     - **url**: The full URL as written in the resume. Normalize to `https://` if it starts with `http://`. Remove trailing slashes.
+     - **username**: Extract the last path segment or handle from the URL:
+       - `https://github.com/username` → username = "username"
+       - `https://linkedin.com/in/username` → username = "username"
+       - `https://twitter.com/username` → username = "username"
+   - **CRITICAL**: ONLY extract URLs that are EXPLICITLY present in the resume. Do NOT add any default or assumed profiles.
+   - Do NOT add generic platform homepages (e.g., don't add "https://github.com" unless the candidate has a personal GitHub profile link).
+   - If no profile URLs exist, return an empty array `[]`.
+
+**VALIDATION CHECKS BEFORE RETURNING:**
+- Email must pass basic format validation (contains @ and domain with .)
+- Phone number must be digits only, possibly starting with +
+- All URLs must start with http:// or https://
+- profiles array is never null — always [] when empty
+- location.city may be null but if countryCode is set, city should also be populated
+
+**WHAT TO IGNORE:**
+- Address components like "flat #", "street", "landmark" — they are not part of the JSON Resume basics schema.
+- Social media handles that are NOT URLs (e.g., "@amitsharma" without a URL).
+- Phone numbers in non-contact sections (e.g., mentioned inside a project description).
+
+**IMPORTANT**: Return ONLY valid JSON. Do not include any explanatory text, markdown code fences, or surrounding comments.
 
 --- The input resume markdown starts here ---
 
 {{ text_content }}
 
 --- The input resume markdown ends here ---
-
-Return ONLY a JSON object with this structure:
-{
-  "basics": {
-    "name": "Full name",
-    "email": "Email address", 
-    "phone": "Phone number",
-    "url": null,
-    "summary": null,
-    "location": {
-      "city": "City",
-      "countryCode": "Country code"
-    },
-    "profiles": [
-      {
-        "network": "Platform name",
-        "url": "Full URL",
-        "username": "Username from URL"
-      }
-    ]
-  }
-}
-
-**IMPORTANT**: If there is any About Me or Summary section, add that to the summary section of the basics
-
-**CRITICAL**: For profiles section:
-- ONLY extract URLs that are EXPLICITLY present in the resume markdown
-- Look for URLs in markdown format [text](url) or plain URLs
-- DO NOT create any URLs that are not in the original resume
-- DO NOT add generic platform URLs like "https://github.com" or "https://linkedin.com" unless they are actually present in the resume
-- If no URLs are found in the resume, return an empty profiles array: "profiles": []
-- If a URL is present but you cannot determine the network or username, still include it with the available information
-- If the URL is of the format github.io or personal domain, mark the network as "Portfolio"
-- If there is any link at the header of the resume or Portfolio link, add that as url in the basics
-
-**EXAMPLES OF WHAT NOT TO DO:**
-- Do NOT add "https://github.com" if GitHub is not mentioned in the resume
-- Do NOT add "https://linkedin.com" if LinkedIn is not mentioned in the resume
-- Do NOT add "https://leetcode.com" if LeetCode is not mentioned in the resume
-- Do NOT add "https://stackoverflow.com" if Stack Overflow is not mentioned in the resume
-
-**EXAMPLES OF WHAT TO DO:**
-- If resume contains "GitHub: https://github.com/username", extract it
-- If resume contains "[My Portfolio](https://example.com)", extract it
-- If resume contains "LinkedIn: linkedin.com/in/username", extract it
-
-**IMPORTANT**: Return ONLY valid JSON. Do not include any explanatory text. 
-

prompts/templates/education.jinja

@@ -1,23 +1,81 @@
-Extract ONLY the education information from this resume.
+You are an expert resume parser specializing in extracting education history from resumes. Your job is to extract ONLY the education section — degrees, certifications, courses, and academic achievements — and return it as a valid JSON array of education objects conforming to the JSON Resume education schema.
 
---- The input markdown starts here ---
+**EDUCATION ENTRY STRUCTURE (each degree/course gets one object):**
+
+Each extracted education entry must contain these fields:
+
+1. **institution**:
+   - The name of the school, university, college, or training organization.
+   - Preserve the official name exactly as written: "Indian Institute of Technology, Bombay" not "IIT Bombay" (unless only the short form is present).
+   - If the institution has a branch/campus (e.g., "University of California, Berkeley"), include the full name.
+   - For online platforms (Coursera, edX, Udemy), use the platform name as the institution: "Coursera", "edX", "Udacity".
+
+2. **area**:
+   - The field of study or specialization: "Computer Science", "Electrical Engineering", "Data Science".
+   - For certifications: the certification title/topic area: "AWS Solutions Architect", "Google Cloud Professional".
+   - If no specific area is mentioned but the degree name implies one (e.g., "B.Tech"), derive it: "Technology" or the specialization if listed.
+   - Do NOT leave this blank — if completely missing, infer from the degree type as a best effort (but never invent).
+
+3. **studyType**:
+   - Normalize to standard degree types:
+     - "Bachelor of ..." for B.Tech, B.E., BSc, BA, BTech, BS
+     - "Master of ..." for M.Tech, M.E., MSc, MA, MS, MBA
+     - "PhD" or "Doctorate" for PhD, Doctor of Philosophy
+     - "Diploma" for diploma programs
+     - "Certificate" / "Certification" for short courses and professional certs
+     - "Course" for individual course enrollments
+   - If the resume uses non-standard terms (e.g., "Graduate Programme"), normalize to the closest standard type.
+
+4. **startDate**:
+   - Use the format `YYYY-MM` or `YYYY` if only the year is available.
+   - For "2021 – Present" or "2021-Present": startDate = "2021-01", endDate = `"present"`.
+   - If only a start year is given and no end date, set startDate to `"YYYY-01"` and leave endDate as `null` (candidate may still be studying).
+
+5. **endDate**:
+   - Use the format `YYYY-MM` or `YYYY`.
+   - For ongoing education: `"present"`.
+   - For "Completed in 2023": endDate = "2023-12" (use December for year-only graduations).
+   - If no end date is given and it's a past degree, infer from typical duration:
+     - Bachelor's: start + 4 years
+     - Master's: start + 2 years
+     - But ONLY if the resume indicates completion. If ambiguous, leave as `null`.
+
+6. **score**:
+   - Extract GPA, CGPA, percentage, or any academic score exactly as reported.
+   - Normalize the scale indicator: "9.2/10" → score = "9.2", additional context can go into a notes field if needed.
+   - For percentages: "85%" → score = "85", note the "%" in your parsing but return just the numeric string.
+   - For grade-based systems (A+, B, First Class): extract the grade as-is.
+   - If no score is mentioned, return `null`. Do NOT calculate or assume CGPA from marks.
+
+**EXTRACTION RULES:**
+
+1. **SORTING**: Return education entries in REVERSE CHRONOLOGICAL order (most recent/relevant first). Current degrees come before past degrees; master's before bachelor's.
+
+2. **MULTIPLE ENTRIES**: A candidate may have multiple education entries:
+   - Each degree = one entry (e.g., B.Tech is one, M.Tech is another)
+   - Each certification = one entry
+   - Do NOT merge two distinct degrees into one entry.
+
+3. **RELATED FIELDS**: If an institution field contains both a university and department/faculty (e.g., "Department of Computer Science, IIT Bombay"), extract the INSTITUTION as "IIT Bombay" and area as "Computer Science".
+
+4. **THESIS/DISSERTATION**: If the resume mentions a thesis title or dissertation topic within an education entry, include it in the `courseName` or add it as additional context — but ONLY if explicitly stated.
+
+5. **RELEVANT COURSEWORK**: If the resume lists "Relevant Courses" under an education entry, treat this as contextual information and do NOT create separate entries unless each course is individually described with a grade/score.
+
+**WHAT TO SKIP:**
+- High school education unless the candidate has no college/university degree (for intern positions, focus on higher ed).
+- "Pursuing" or "In progress" without any start date — these are incomplete and should be skipped.
+- Self-study mentions without a formal institution: "Self-taught Python via YouTube" — skip entirely.
+
+**VALIDATION CHECKS:**
+- All startDate values must be valid YYYY or YYYY-MM format.
+- No duplicate entries (same institution + same area + same studyType).
+- endDate cannot be before startDate for any entry.
+
+**IMPORTANT**: Return ONLY a JSON array of education objects wrapped in an object with the key "education". Do not include any explanatory text, markdown code fences, or surrounding comments.
+
+--- The input resume markdown starts here ---
 
 {{ text_content }}
 
---- The input markdown ends here ---
-
-Return ONLY a JSON object with this structure:
-{
-  "education": [
-    {
-      "institution": "School/University name",
-      "area": "Field of study",
-      "studyType": "Degree type",
-      "startDate": "Start date (YYYY-MM)",
-      "endDate": "End date (YYYY-MM)",
-      "score": "GPA/Percentage"
-    }
-  ]
-}
-
-**IMPORTANT**: Return ONLY valid JSON. Do not include any explanatory text. 
+--- The input resume markdown ends here ---