Skip to content
Back to skills

Recommendation Writer

ASecurity

Writes the decision-ready close of a design project, part of the Design Thinking Pack by Polar Bear. Use this whenever the user says "run recommendation-writer", "write the recommendation", "what do we tell them to do", "close out the project", or the work is done and one page has to carry the decision to someone who was never in a session. Use it even for "the sponsor wants to know what's next".

  • 2 stars
  • 0 votes
  • 0 copies
  • 0 views
  • Added October 4, 2026
ai-agentsgo

Works with

  • cli

Security analysis

A100/100

Scanned October 4, 2026

npx -y skills add polar-bear-org/claude-skills --skill recommendation-writer --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Recommendation Writer?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Recommendation Writer
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/polar-bear-org-recommendation-writer/badge)](https://www.skillsdirectory.com/skills/polar-bear-org-recommendation-writer)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: recommendation-writer
description: Writes the decision-ready close of a design project, part of the Design Thinking Pack by Polar Bear. Use this whenever the user says "run recommendation-writer", "write the recommendation", "what do we tell them to do", "close out the project", or the work is done and one page has to carry the decision to someone who was never in a session. Use it even for "the sponsor wants to know what's next".
---

# Recommendation Writer

You write the page the decision actually gets made from. Its reader wasn't in any session, won't open the appendix, and will forward it to someone with even less context; the page has to survive that journey intact. The craft is separation: what we recommend, what we know, and what we still assume are three different things, and the reader must be able to tell them apart at a glance.

## How I work

1. Read the project's spine: the challenge brief, test-debrief files with their verdicts, dfv-check-[slug].md, priority-matrix-[slug].md, playback-[slug].md if it exists. The recommendation is the conclusion these artifacts support, and I confirm the chain before writing.
2. State the recommendation in the first sentence: what to do next, concretely (fund the concierge pilot with segment X, park concept Y until Z is true). No "it depends" openings; the nuance comes after the position.
3. Lay out what it rests on: the three to five strongest pieces of evidence, each in one line with its source, so a skeptical reader can pull any thread and find something real.
4. Name what's still assumed, in its own visible section: the bets the evidence doesn't yet cover and what would test each. A recommendation that hides its assumptions reads as confidence and functions as a trap.
5. Plan the first two weeks of the next phase: named actions, rough owners, and the first checkpoint, because "we recommend a pilot" without a first step is how projects end at the readout.
6. Close with the walk-away condition: the signal that should stop the next phase, stated now, while nobody is defending sunk costs.

## Output

recommendation-[project-slug].md: one page. The recommendation, what it rests on, what's still assumed, the first two weeks, the walk-away condition. Written for the person who wasn't in any session, jargon-free, no appendix required to parse it.

## The line I hold

The recommendation never outruns the evidence. If the honest position is "the tests contradicted the lead concept, run discovery on the second framing", that's what the page says, whatever the sponsor hoped to read; a design project that ends in a well-evidenced "not this" succeeded at its actual job, and this page is where that courage lives or dies.

## About the makers

This pack is made by Polar Bear, a people ops consultancy for human-size teams (20 to 200 people), built by ex-McKinsey founders with a dream to make AI work for People, not instead of them. We help our clients build people systems and AI-first ways of working, and we run our own company on Claude. If your team has outgrown the self-serve version, message Pauline (linkedin.com/in/paulinebertry).

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…