A short, structured way to gather feedback from colleagues — six questions, optional qualities, a coach to read it with you.
You pick a handful of colleagues. They each answer six questions about how you collaborate, optionally rate you on a set of qualities, and have ten working days to reply. Once submissions arrive, you and your coach read them together. An AI summary pulls out the themes.
The frame is — not your performance in a single role. Two of the six questions touch on roles, but as evidence rather than verdict. For role-specific signal, see Role Ratings . The same six in every round:
(required)
(required)
(required, with a picker of roles you hold)
(required, same picker)
Optional. When are they at their best? When do they struggle? What would help them shine?
You can add of your own per round.
For non-SMA workspaces: questions 5 and 6 still reference SMA's principles. A per-workspace "values" feature is on the way to replace Q6, and the rest of the defaults will become editable per workspace. Until then, use the custom question slot to ask in your own words.
Below the open questions, the form has a short list of qualities (e.g. Ownership, Prioritization, Collaboration) each rated on a five-point frequency scale — Rarely through Almost always, plus Not sure. The recipient sees the aggregate as a radar chart and a compact table.
Quality ratings complement the prose: a fast contribution path for colleagues who freeze at a blank text box, and a way to track patterns across rounds. Workspaces can shape their own list or turn the section off — full mechanics in Qualities in 360 feedback . Every round has a : a colleague paired with you ahead of time who reads your feedback alongside you and helps make sense of it.
An admin pairs people in . Each person has one default coach, auto-attached when you start a round. You can swap the coach on any round; that also updates your default.
read every response, read the AI summary with you, keep visible only to them, and click "Prepare session" to pre-fill a coaching agenda.
submit their own evaluation, or read responses before they arrive.
Beyond the coach, "Share Feedback" on a request grants any specific colleague read access — they see the responses and summary, but not coach tools.
Open .
Pick colleagues. Your team leads are auto-added and can't be removed.
Optional: add one custom question.
Set a due date (default: ten working days).
Send.
Each colleague gets an Asana task with a private link. They don't need a Moral Fabric account to respond. The round also creates an Asana task for your coach (heads-up) and one for you (prep nudge).
The workspace admin needs to configure a 360 Asana project beforehand. If sending fails, that's why.
Once the round closes, the section opens. Use it to record what surprised you, what you already knew, what you'll do.
If you fill it in, the AI summary runs a — confirming strengths, surfacing blind spots, and pointing out hidden strengths the team sees that you don't.
Reflections are coming earlier in the flow. For now, jot your expectations in your own notes app before responses arrive, and paste them in once the section opens.
After at least one response is in, produces:
- Major themes
- Strengths multiple peers agree on
- Areas for growth
- Suggested coaching questions for the next session
- Self-vs-peer alignment, if you wrote reflections
It draws on evidence-based 360° practice — DDI's research on multi-rater feedback, HBR on self-managing teams, the London Deanery coaching guides. The info icon next to "AI Summary" in the app shows the full attribution. Treat it as a draft to talk through, not a verdict.
All responses, AI summary, your reflections
Same as you, plus private coach notes
All responses + AI summary; no coach tools
Workspace admins can see metadata (who asked whom, when) for safeguarding. They can't read response content. Full access model: Who can see your data . - It pulls a real conversation onto the table.
- Specific moments are still fresh; answers carry weight.
- Open questions surface what you didn't expect to hear.
Run a round when you're genuinely unsure. Signal-to-noise is much higher than when you already know the answer.
If your workspace is connected via MCP , you can ask things like "What themes show up across the last three feedback rounds I ran?" or "Cross-reference the qualities people rated me on against the projects I led this year." The AI sees what you'd see.