Triggers on "prepare for interview", "interview prep", "preparar entrevista", "mock interview". Builds an interview preparation kit with question banks, STAR frameworks, company research checklists, and follow-up templates. Output: prep document. [EXPLICIT]
From jm-adknpx claudepluginhub javimontano/jm-adk-alfaThis skill is limited to using the following tools:
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Searches prompts.chat for AI prompt templates by keyword or category, retrieves by ID with variable handling, and improves prompts via AI. Use for discovering or enhancing prompts.
Designs and optimizes AI agent action spaces, tool definitions, observation formats, error recovery, and context for higher task completion rates.
Produces a structured interview preparation document tailored to a specific role and company. Includes a categorized question bank, STAR-method response scaffolds, company research checklist, talking points aligned to job requirements, and post-interview follow-up templates. Works for job interviews, client discovery calls, and stakeholder meetings.
Do NOT activate for resume writing (cv-enhancement), salary negotiation strategy, or job search planning (those are separate skills).
Extract and organize from the user's input:
| Field | Source | Evidence Tag |
|---|---|---|
| Role title | Job posting/user | [EXPLICIT] |
| Company name | Job posting/user | [EXPLICIT] |
| Interview type | User/inferred | [EXPLICIT] or [INFERRED] |
| Key requirements | Job posting | [EXPLICIT] |
| Nice-to-haves | Job posting | [EXPLICIT] |
| Culture signals | Job posting/web | [INFERRED] |
| Interviewer details | User provided | [EXPLICIT] or [OPEN] |
Map the candidate's likely strengths to each listed requirement:
| Requirement | Candidate Evidence Point | Confidence | Gap? |
|---|---|---|---|
| 5+ years experience | Specific role/project | High/Med/Low | Y/N |
| Leadership experience | Team size, scope | -- | -- |
| Technical skill X | Project, certification | -- | -- |
Flag gaps explicitly — these become areas for proactive framing in answers.
Questions probing past behavior as predictor of future performance:
For each question, provide:
Role-specific knowledge and problem-solving:
Forward-looking scenarios:
Strategic questions that demonstrate preparation and genuine interest:
For the top 5 most likely questions, build complete STAR scaffolds:
Question: [specific question]
Competency tested: [what they are evaluating]
S — Situation: [context setting, 1-2 sentences]
T — Task: [your specific responsibility]
A — Action: [what YOU did, step by step — this is the longest section]
R — Result: [quantified outcome + lesson learned]
Transition: [how this connects to the role you are interviewing for]
Rules for STAR responses:
Thank-you email (send within 24 hours):
Follow-up after no response (send after 5-7 business days):
| Decision | Option A | Option B | Recommendation |
|---|---|---|---|
| Preparation depth | Cover all question types | Deep-dive on top 5 | Deep-dive — mastery beats breadth |
| Response style | Scripted answers | Bullet-point scaffolds | Scaffolds — sound natural, not rehearsed |
| Company research scope | Exhaustive | Focused on role context | Focused — show targeted knowledge |
| Questions to ask | Many prepared | 3-4 strong ones | 3-4 strong — quality signals preparation |
| Mock practice | Solo rehearsal | With a partner | Partner preferred — feedback loop matters |
[INFERRED] and flag lower confidence.Role: Senior Product Manager at Acme Corp
Interview type: Behavioral + Case Study (Round 2)
Question: "Tell me about a time you had to make a product decision with incomplete data."
Competency: Decision-making under ambiguity
S — Led pricing redesign for SaaS platform serving 2,000 customers.
T — Had to decide between usage-based and tier-based model with only 60% of customer data analyzed.
A — Built a lightweight conjoint survey for top 50 accounts, ran 2-week pilot with both models on a cohort, synthesized directional signals.
R — Tier-based model won with 23% higher expansion revenue in pilot. Shipped to all customers, validated at scale within 90 days.
Transition — Acme's product decisions likely require similar speed-vs-rigor tradeoffs given your growth stage.
Evidence: [EXPLICIT] from job posting emphasis on "data-informed but action-oriented"
Question: Tell me about yourself.
Answer: I have 10 years of experience and am passionate about products.
(No structure, no specifics, no connection to role, no evidence tag)
Before delivering the prep document, confirm every item:
[EXPLICIT], [INFERRED], or [OPEN]| File | Purpose |
|---|---|
references/star-framework.md | STAR method deep-dive with anti-patterns and timing guide |
references/question-banks.md | Master question bank by competency category and seniority level |
references/followup-templates.md | Email templates for thank-you, follow-up, and rejection response |