Career Job Fit Evaluator

Job Fit Evaluator

Overview

Assess job opportunities against the user's stored CV, target profile, and fit rubric. Produce a practical decision that explains compatibility, gaps, risks, and how to position the user's experience.

Required References

Before evaluating a role, read:

• references/cv.md for the user's background, experience, skills, achievements, education, languages, and constraints.
• references/target-profile.md for desired roles, industries, seniority, work model, compensation, and non-negotiables.
• references/evaluation-rubric.md for scoring rules and output format.

If any reference still contains placeholder text, say what is missing and continue with a provisional assessment using only the available information.

Workflow

1. Read the required references.
2. Parse the job post into:
   • role title and seniority
   • core responsibilities
   • required qualifications
   • preferred qualifications
   • technical skills, domain skills, languages, and tools
   • location, remote policy, contract type, compensation, and schedule if present
3. Compare the role against the CV and target profile.
4. Score fit using references/evaluation-rubric.md.
5. Return a clear recommendation:
   • Strong fit
   • Possible fit
   • Stretch
   • Not recommended
6. Ground every major conclusion in evidence from the CV, target profile, or job post. Do not invent experience.

Evaluation Guidance

• Treat "required" criteria as more important than "preferred" criteria.
• Distinguish direct experience from adjacent or transferable experience.
• Consider seniority fit: under-leveling, right-leveling, and over-leveling.
• Do not over-trust job titles. In technology roles, titles can be disconnected from the real job; evaluate the responsibility mix, scope, stakeholders, outcomes, and operating model first.
• Flag dealbreakers from the target profile even when the experience match is strong.
• Apply conservative scoring. Do not inflate the 0-100 score to be agreeable; high scores require direct evidence and no major hard-requirement gaps.
• Treat mandatory education, credentials, licenses, and background requirements as real constraints. If the requested formation is far from technology, design, product, digital, or exact sciences, apply the rubric's stronger penalty/cap.
• Call out missing evidence separately from true skill gaps.
• Be candid but helpful: if the role is weak, explain why and suggest better role keywords or titles.
• If the user asks in Portuguese, answer in Portuguese. Otherwise, match the language of the user's request.

Output

Use this concise structure unless the user requests another format:

**Decision:** <Strong fit | Possible fit | Stretch | Not recommended>
**Fit Score:** <0-100>
**Confidence:** <High | Medium | Low>

**Why**
- <Evidence-based reason>
- <Evidence-based reason>

**Matched Experience**
- <Job requirement> -> <matching CV evidence>

**Gaps / Risks**
- <Gap, risk, or missing evidence>

**Score Inhibitors**
- <Main reasons the score is not higher, especially mandatory education, credentials, seniority, language, tools, or domain gaps>

**Application Strategy**
- <How to position the user's background>
- <CV/profile keywords to emphasize>

**Better-Fit Search Terms**
- <Role titles, keywords, or industries if useful>