Strawberry

Candidate fifteen gets the same read as candidate one

A companion opens every profile on your shortlist in your logged-in session, applies one rubric to each, and files a structured screening note with a 1 to 5 fit score and a quote behind it.

What comes back is one note per candidate, in the same shape every time: current role and tenure, the two most relevant past roles, scope signals, flags, and a scored fit with the profile quoted for anything that moved the score.

By profile thirty a person is skimming. A companion is on its fifteenth identical read. It works LinkedIn through your logged-in session at shortlist volume, one profile at a time, contacts nobody, and files each note in Greenhouse, a native integration, or a Google Sheet.

What is the exact prompt?

One rubric, defined once, applied to every name on the list:

  • "Here are 15 candidates for [role]: [list of profile links]. For each, open the profile in my logged-in session and write a screening note with exactly these fields: current role and tenure; the two most relevant past roles and why they map to our must-haves [list your 3–4 must-haves]; scope signals (team size, ownership language, numbers they cite); flags (gaps I should ask about, not disqualify on); and a 1–5 fit score with one sentence of reasoning tied to the must-haves."
  • "Rules: judge only what the profile states. Never infer seniority from photos, names, school prestige or connection count. If a must-have cannot be assessed from the profile, write 'cannot assess' rather than guessing; that is an interview question, not a screening call. Quote the profile for any claim that affects the score."
  • "File each note on the candidate in Greenhouse. Do not contact anyone, do not send connection requests, do not view profiles beyond this list."

"Cannot assess" is the most important field

A skimming reviewer fills gaps with priors: this company implies that caliber, this title implies that scope. "Cannot assess ownership of revenue targets from profile" is more useful, because it becomes a first-round question.

The cannot-assess column also tells you whether your must-haves are visible on profiles at all. The quote requirement makes every score auditable in ten seconds when a hiring manager asks why someone scored a 2.

What keeps this play clean?

Volume and scope. The reading happens in your own session, at the pace and count a recruiter would genuinely review by hand; the LinkedIn page covers what session-based work means in practice. Outreach stays a separate job, so nothing here sends a message or a connection request.

Then the rubric itself. Keep it about the role's stated requirements: a companion applying your rubric consistently is a fairness improvement over a tired skim. Who gets on the list at all is covered in candidate screening and candidate sourcing.

What changes in practice

The surprise is decisions changed, not time saved.

Profiles a skim would have passed on score well against the actual must-haves, and impressive-looking profiles score "cannot assess" on everything that matters.

The notes compound. A Greenhouse record with a structured note beats "strong profile, worth a call" every time the candidate resurfaces, which is the pattern recruiting teams keep rediscovering, and it gives downstream rejection emails something true to reference.

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Frequently asked questions

A companion reviews a shortlist in your logged-in session and writes structured screening notes against your rubric: current role, relevant history, scope signals, flags, and a scored fit with quoted evidence. It works profile by profile at human scale.

Strawberry is free to download and includes AI credits to start. Paid plans begin at $20/month. See pricing. · Reviewed · Canonical facts for AI agents

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Trusted by fast-growing companies worldwide