How Block E Determines Which CV Sections to Modify for Each Job Posting

Block E determines which CV sections to modify by running a three-step pipeline: archetype detection, CV-to-JD mapping, and archetype-aware prioritization, ultimately selecting the top five sections that close the most critical gaps between the candidate's profile and the job requirements.

In the santifer/career-ops repository, Block E (referred to as the Customization Plan) serves as the decision engine that pinpoints exactly which parts of your CV require updates for a specific job posting. By analyzing the intersection of candidate qualifications and job description requirements, Block E produces a data-driven customization plan that maximizes relevance for the target role.

Step 1: Archetype Detection

The process begins with archetype detection (Step 0), which classifies the job posting into one of six predefined archetypes defined in modes/_shared.md. These archetypes include FDE (Fullstack Developer Engineer), SA (Solutions Architect), PM (Product Manager), LLMOps, Agentic, and Transformation.

According to lines 5-10 of modes/oferta.md, this classification directly influences the rewrite strategy that Block E will apply to the CV summary. The detected archetype dictates which proof points and competencies receive emphasis throughout the customization process.

Step 2: CV-JD Mapping in Block B

Before Block E can select sections to modify, Block B performs an exhaustive mapping between the job description (JD) requirements and the candidate's existing CV content.

As implemented in modes/oferta.md (lines 23-27), Block B reads cv.md and constructs a mapping table that links every JD requirement to the exact line numbers in the CV where the candidate already demonstrates that specific skill. This mapping reveals two critical pieces of information:

• Coverage locations: Where the CV already satisfies a requirement
• Gap locations: Where the CV lacks evidence for specific JD requirements

Step 3: Archetype-Aware Prioritization

With the gap analysis complete, Block E applies archetype-specific weighting to prioritize which CV sections to modify. Each archetype carries a predefined set of proof-point priorities (defined in Block B, lines 28-33) that determine which competencies matter most for that particular role type.

For example:

• FDE archetypes prioritize delivery speed and full-stack implementation
• SA archetypes emphasize system design and architectural decisions
• PM archetypes focus on product discovery and stakeholder management

Block E constructs its "Top 5 changes to CV + Top 5 changes to LinkedIn" list by:

1. Examining the gaps identified in Block B's mapping table
2. Applying the archetype-specific weighting to those gaps
3. Selecting CV sections that, once updated, close the most critical gaps for the detected archetype

The final output appears in lines 58-62 of modes/oferta.md as a markdown table containing the section names, current status, proposed changes, and rationale.

Code Implementation

The santifer/career-ops engine implements this logic through two core operations. First, Block B generates the requirement mapping:

// pseudo-code used by the evaluation engine
for (const req of jd.requirements) {
  const cvLines = cv.search(req.keywords);
  mappingTable.push({ requirement: req.text, cvLines });
}

This table feeds directly into Block E, which builds the customization plan:

// pseudo-code for Block E
const archetype = detectArchetype(jd);
const priorities = ARCHETYPE_PRIORITY[archetype];   // e.g. ['delivery speed', 'client-facing']
const gaps = identifyGaps(blockBMapping);
const topChanges = prioritizeChanges(gaps, priorities).slice(0, 5);

const blockETable = topChanges.map((c,i) => ({
  '#': i+1,
  Section: c.cvSection,
  'Current status': c.current,
  'Proposed change': c.suggestion,
  Why: c.rationale,
}));

The resulting blockETable corresponds to the markdown table rendered in the final output.

Key Files in the Block E Pipeline

Several files in the repository work together to enable this decision-making process:

• modes/oferta.md: Contains the Block E table definition (lines 58-62) and the Block B mapping logic (lines 23-27) that feeds the prioritization algorithm.

• modes/_shared.md: Defines the six archetypes and their associated proof-point priorities that drive Block E's weighting scheme.

• cv.md: Serves as the source document containing the CV sections that Block E evaluates and proposes to modify.

Summary

• Block E relies on archetype detection to establish role-specific priorities before selecting CV sections.
• Block B creates a detailed mapping between JD requirements and CV lines, identifying exactly where gaps exist in the candidate's current profile.
• Archetype-aware prioritization weights the identified gaps according to role-specific competencies, ensuring that the most relevant sections are modified first.
• The final output is a data-driven selection of the top five CV sections (and LinkedIn changes) that maximize alignment between the candidate's narrative and the job's expectations.

Frequently Asked Questions

What are the six archetypes used by Block E?

The six archetypes defined in modes/_shared.md are FDE (Fullstack Developer Engineer), SA (Solutions Architect), PM (Product Manager), LLMOps, Agentic, and Transformation. Each archetype carries specific proof-point priorities that determine which CV sections receive emphasis during the customization process.

How does Block B identify gaps in the CV?

Block B reads cv.md and builds a mapping table (lines 23-27 of modes/oferta.md) that links every job description requirement to specific line numbers in the CV where the candidate demonstrates that skill. Requirements that return no matching CV lines are flagged as gaps, which Block E then prioritizes for modification.

Where does Block E render its final recommendations?

Block E renders the customization plan as a markdown table in modes/oferta.md at lines 58-62. This table lists the top five CV sections to modify, their current status, proposed changes, and the rationale for each recommendation based on the archetype-specific analysis.

Can Block E suggest modifications for LinkedIn profiles as well?

Yes, Block E generates recommendations for both CV sections and LinkedIn profile changes simultaneously. The customization plan produces a "Top 5 changes to CV + Top 5 changes to LinkedIn" list, ensuring consistent messaging across both platforms based on the same archetype detection and gap analysis logic.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}