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Recruiting & Onboarding

Candidate dossier for the next interview loop

Everything the team has ever said about this candidate, surfaced in one place.

Best for
Pre-loop sync
Primitives
ActorsInteractionsStance
Token savings
60%

The prompt

You are preparing the interview loop for {{candidate_name}}. Using Sentra: 1. Resolve {{candidate_name}} as an Actor — match across ATS, calendar invites, email threads, prior Slack mentions, and any referral source. 2. Pull every internal Interaction where the candidate has been discussed, ordered by date. 3. For each prior interviewer, extract their stance, their concern (if any), and the dimension they evaluated. 4. Pull external-source context: referral notes, recruiter intake, prior loop notes if any. Output: - Snapshot card: name, role, level under consideration, source, recruiter, hiring manager. - Interviewer map: who they've already met, the dimension covered, the stance. - "What's still open" — the dimensions not yet evaluated, mapped to the panel members who will cover them. - Three suggested probing questions per remaining interviewer based on prior concerns.

See it work

Run it from

ClaudeCursorChatGPTAny agent · MCP

How it runs

  1. 01Copy the prompt into any agent connected to Sentra over MCP.
  2. 02The agent reads the company memory, scoped to what you are allowed to see.
  3. 03One grounded answer comes back, with every line traceable to its source.

Or automate it with Actions

The same prompt runs as a Sentra Action: on a schedule, or on a semantic trigger. Output lands in Slack or email, and every send waits for your approval.

Trigger idea: pre-loop sync

Sentraover MCPEverything the team has said, in one place

Candidate R. Okafor · loop 2 prep

Panel so far

debriefs · 2

Systems round: strong hire, praised failure-mode reasoning. Hiring-manager screen: positive with a flag on scope ambiguity in the last role.

Already asked

interview notes

The failure-mode scenario and the migration war story are used; round two should probe team leadership instead.

Open concern

Depth is proven; breadth across the stack is the untested axis. The panel disagreement is exactly there.

The prompt above becomes this. Fictional data, real mechanics: every line cites the meeting, thread, or record it came from.

Without Sentra

  1. 01Pull the candidate's record from the ATS. Parse role, source, recruiter, prior loops.
  2. 02Search Gmail for messages with the candidate's address. Skim every thread.
  3. 03Search Slack DMs and channels for mentions of the candidate's name. Filter to material posts.
  4. 04Pull calendar events the candidate has attended. Read meeting notes.
  5. 05For each prior interviewer, search their feedback artifact — scorecard, notes, DM to recruiter.
  6. 06Manually extract per-interviewer stance, concern, and evaluated dimension.
  7. 07Compose the dossier.

~80,000 tokens

With Sentra

  1. 01Resolve the candidate as an `Actor` — joined across ATS, calendar, email, and Slack mentions.
  2. 02Pull every internal `Interaction` discussing them, ordered by date.
  3. 03For each prior interviewer, typed `stance`, `concern`, and evaluated dimension are extracted.
  4. 04Pull source and recruiter context from the candidate's `Actor` relations.
  5. 05Compose the dossier.

~32,000 tokens

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