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Turn a job description into an interview kit

Paste any job ad. We'll extract the competencies that actually matter, then build you a tailored set of interview questions and a scorecard.

Runs entirely in your browser. The JD never leaves your device.

The full ad works best — title, responsibilities, requirements. We look for behavioural signals, not just keywords.

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1

Paste any JD

Job ad, role spec, recruitment brief. No formatting required.

2

Get matched competencies

We score 28 competencies against the JD's behavioural signals and rank the strongest matches.

3

Generate questions or scorecard

One click sends the matched competencies to the STAR Question Generator or Scorecard Builder.

Why competency extraction matters

The single biggest mistake in interview design is asking the same generic questions regardless of the role. A "leadership" question for a senior manager hire and for a graduate engineer should be radically different — and most JDs already tell you which competencies to prioritise, if you know what to look for.

This tool does the boring bit for you: it scans for behavioural signals (verbs, responsibilities, working conditions) and ranks the 28 competencies most strongly suggested by the language of the role itself. You can adjust before generating — you know the role, we just give you a strong starting point.

No JD content is sent anywhere. The entire analysis runs in your browser.

Common questions

Is this AI?

No. It's a deterministic phrase-matching engine — every competency has a curated set of trigger phrases and the JD is scored against them. That makes it fast, free, predictable, and private. No data leaves your browser, no API calls, no surprises.

How accurate is it?

Good enough to be a strong starting point, not a final answer. The point is to get you 80% of the way there in seconds, then let you adjust the last 20% based on what you actually know about the role. You can always add or remove competencies before generating.

My JD is in another language. Will it work?

Right now, English only. The trigger phrases are English-language. If there's demand for other languages, we'll add them.

Can I use this for senior or executive roles?

Yes — the tool detects strategic, leadership, and stakeholder competencies as readily as junior-role ones. For C-suite hires, you'll likely want to add competencies the tool didn't pick up (vision, board management, P&L ownership) using the custom-competency option in the STAR Generator.

Why analyse a job description before you interview?

Most job descriptions are written in a hurry, copied from the last open role, and stuffed with everything HR, the hiring manager, and the team lead each thought they wanted. By the time the interview rolls around, nobody remembers which of those requirements actually matter — so the panel ends up assessing whichever ones they personally rate highest. That's how you get five interviewers producing five completely different scoring patterns from the same JD.

Analysing the JD upfront forces a different question: which of these competencies will actually predict whether someone succeeds in this role? This tool reads the language of your JD — the verbs, the responsibilities, the seniority cues — and surfaces the competencies that the document is genuinely asking for, ranked by how strongly the JD argues for each one. It's not magic and it's not AI. It's a deterministic phrase-matcher built on 28 evidence-based competencies and roughly 280 weighted triggers, so the same JD always produces the same answer.

How to read the results

Strong matches (top of the list)

These are the competencies the JD makes a sustained, explicit case for. If the JD repeatedly references "ownership", "driving outcomes", and "ambiguity", expect resilience and proactivity to score high. These are the competencies you should build your interview around — pick four to six and treat them as your assessment spine.

Moderate matches (middle)

Competencies the JD touches on but doesn't lean into. Useful as secondary assessment criteria — usually worth one question or one scorecard line, not a whole interview round.

Weak or no matches (bottom)

Competencies the JD doesn't argue for. Don't add them just because they sound nice. The whole point of an evidence-based interview is to assess what this role needs, not your generic checklist of "good employee" traits.

What this tool will and won't do

Common JD problems this analysis surfaces

The "everything-and-the-kitchen-sink" JD

If 12 competencies all score similarly, the JD is asking for too much. That's a red flag for the role itself, not the analysis. Real roles have priorities. Push back on the hiring manager: which three of these are actually non-negotiable?

The "title vs content" mismatch

If you've posted "Senior Customer Success Manager" but the JD reads like a junior account coordinator, the competency mix will tell you. Useful before you waste recruiting cycles.

The "technical role described in soft-skill language"

If the JD is for a senior engineer but scores high on collaboration and low on technical proficiency, somebody's papered over the technical bar with culture-fit language. Worth a conversation before the first phone screen.

Where this fits in your hiring workflow

The JD Analyser is step one. Once you've got your competencies, the two CTA buttons at the top of your results will route you directly into the Scorecard Builder (with the competencies and likely role family pre-selected) or the STAR Question Generator (with the same competencies pre-loaded into question generation). One paste, three artefacts: a prioritised competency list, a structured scorecard, and a behavioural question pack. That's the entire pre-interview prep done in about ten minutes.

FAQ

How long does the JD need to be?

Roughly 200 words minimum produces useful signal. Anything shorter and the matcher doesn't have enough to work with. Most real-world JDs are 400–800 words, which is the sweet spot.

Does it work in languages other than English?

Currently English only. The trigger phrases are English-language idioms ("driving outcomes", "stakeholder management", etc.). A French or German version would need its own trigger lexicon — on the roadmap.

Why doesn't it use AI?

Because for this job, AI is overkill and worse. A deterministic engine produces the same answer every time, can be audited, runs in your browser at zero cost, and doesn't hallucinate. The tradeoff is that it can't read between the lines the way an LLM can — but for surfacing what a JD is literally asking for, deterministic wins.

Is the JD sent anywhere?

No. The entire analysis runs locally in your browser. Nothing leaves your device. Anonymous page-view analytics via Plausible only.