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Project User Recommendations

Also available in workflows

This specialist runs in chat and as a node you can add to a workflow for repeatable, scheduled runs. See the Agent Catalog for how the two relate.

Overview​

Project User Recommendations helps you staff a project with the right people. Describe what the project needs and give Ellie a pool of candidates with their skills, and it identifies the top three best-fit people — ranked, scored, and explained.

Ellie weighs three things: how well each person's skills align with the project's requirements, their past performance and reliability, and their availability against competing priorities. It's deliberately disciplined — it won't guess or invent details when information is missing, so the recommendations rest on what you actually provide.

Reach for this when you're forming a project team, assigning an initiative, or deciding who's the strongest fit among several candidates. It replaces a gut call with a scored, side-by-side comparison you can defend.

What you'll need​

  • The project. What it involves and the skills or requirements it demands. The clearer the brief, the sharper the match.
  • The candidate pool. The people to consider, with their skills, proficiency, and — where you have it — performance and availability.
  • Optional context. Timeline, team-size limits, or any must-have skill you can't compromise on.

How to ask​

Describe the project and the candidates.

Recommend the best three people for this data-migration project based on
skill fit and past performance. Project brief and team skills attached.

Add a hard requirement.

Who are our top three candidates to lead this customer-onboarding project?
Stakeholder-management experience is essential. Candidate profiles attached.

Ask for the comparison up front.

Compare these five engineers for the platform-rebuild project and rank the
top three, with each person's skill match and any gaps.

What you get​

A recommendation report built for a staffing decision:

  • Executive summary — the project restated, its key requirements, and an overall confidence level.
  • Top three recommendations — each candidate ranked, with a match score, a breakdown of the skills they meet, and considerations to weigh.
  • Summary table — all recommended candidates side by side, showing rank, match score, confidence, the key skills met, and any skill gaps.
  • Risk assessment — the delivery risks in the recommended staffing and suggested ways to mitigate them.

As a workflow node, the same structured recommendation is produced as an exportable report.

Tips​

  • Spell out the project's required skills clearly — the match scores are only as good as the requirements you give.
  • Include performance and availability where you have them, so the ranking reflects more than skills on paper.
  • Ellie won't fill gaps with guesses; if a recommendation feels thin, it usually means the candidate data was thin.
  • Read the risk assessment before you commit — the strongest-scoring team can still carry a delivery risk worth planning for.
  • Comparing many candidates? Put them all in one request so they're scored against the same brief.