# What Cowork Did For Me > Generates a personal impact report showing what someone actually used Microsoft 365 Copilot Cowork for over a period, the jobs that work was doing, estimated time saved, and its expert-equivalent dollar value, rendered as a polished single-file HTML report they can share or print to PDF. Harvests the person's own Copilot Cowork session history automatically when available, falls back to a short guided interview, and can also import a usage export. Use this skill whenever someone wants to know what Cowork or AI has done for them, build a personal AI impact or ROI report, justify their Copilot Cowork investment or seat, prepare for a performance review or renewal conversation, or asks "what did Cowork do for me," "was Copilot worth it," "how much time has Cowork saved me," or "build my AI receipt." - Skill: `kadns/what-cowork-did-for-me` (Agent Skill, multi-file: 10 files) - Install (CLI): `npx skillmds@latest add kadns/what-cowork-did-for-me` - Raw SKILL.md: https://api.skillmd.com/api/skills/kadns/what-cowork-did-for-me/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Web & Frontend - Author: kadns (https://skillmd.com/u/kadns) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/kadns/what-cowork-did-for-me --- # What Cowork Did for Me Turns a period of Copilot Cowork usage into a personal impact report: what the person worked on, the job each piece of work was doing, estimated time saved, and what that time is worth. Output is a self-contained HTML file they can open, adjust, share, or print to PDF. The person should never need admin access, a licensing dashboard, or an export file to get a useful report. Those are optional upgrades, not prerequisites. ## Pick a mode Try these in order. Do not ask the person to choose, just start with harvest and fall back silently if it is unavailable. 1. **Harvest** (best): read the person's own recent Copilot Cowork sessions to see what they actually worked on. 2. **Interview** (always available): a short guided conversation, no data needed. 3. **Import** (optional): a usage export from the Microsoft 365 Copilot Dashboard or another AI provider, for anyone who has one. --- ## Mode 1: Harvest Read the person's own Cowork session artifacts, the inputs analyzed and outputs produced, from their OneDrive `Documents/Cowork/` folder across the reporting window, to see what they actually worked on. Ask first which period to cover, defaulting to the last 30 days. Walk back through the window far enough to cover it. If the window is not fully covered, say so plainly rather than presenting a partial picture as complete. If session history is unavailable or returns nothing, do not announce a failure. Just move to interview mode: "Let me ask you a few quick questions instead." From the harvested sessions, cluster the work into 5 to 10 recurring workflows. Give each a plain-language name the person would recognize. Then count sessions per workflow across the window. Show the person your clustering before continuing and invite corrections, they know their work better than the transcript does. This confirmation step matters, do not skip it. For each workflow, you still need one thing the sessions cannot tell you: what the work actually produced, in one sentence. Ask for the ones that are not obvious from the session content. --- ## Mode 2: Interview Ask, in this order, keeping it brief: 1. What period should this cover? (default: last 30 days) 2. What do you use Cowork for? Prompt for 4 to 8 recurring things. If they are stuck, offer categories: drafting and editing, research and summarizing, code, meeting notes, spreadsheet or data work, client communication, brainstorming. 3. For each one: roughly how often, and in one sentence, what does it produce? 4. What is your hourly rate, or a rough estimate of what your time is worth? If they decline, skip all dollar figures and build the report on hours alone. 5. What does your Copilot Cowork access cost, if anything? Microsoft 365 Copilot is commonly an employer-provided license (about $30/user/month list); many people have an employer-provided seat at no personal cost. Convert stated frequency into a session count for the window: daily is about 20 sessions a month, a few times a week is about 12, weekly is about 4, occasional is about 2. Say that you are estimating rather than presenting these as counted. --- ## Mode 3: Import If the person has a usage export, run: ```bash python scripts/analyze_usage.py --out workflow_analysis.csv ``` See `references/export-guide.md` for how to pull one, and note that most export paths require an admin, billing, or developer role. Use the real session counts and costs from the export in place of estimates, then continue with mapping below exactly as in the other modes. --- ## Map every workflow (all modes) Read `references/jtbd-taxonomy.md` and assign each workflow four things: - **Business Process**: the function it belongs to, in the person's own organizational language where they offer it - **Job to be Done**: what the work was hired to accomplish, phrased as an outcome starting with a verb, never as a tool - **Value Pillar**: one of Revenue Growth, Cost Reduction, Risk Mitigation, or Transformation - **Category**: one of `analysis`, `document`, `email`, `meeting`, `communication`, `code`, `data`, `other`, which sets the time-saved band Propose your mapping and let the person correct it. Push gently on pillars: most people default everything to Cost Reduction, but review work that catches problems is Risk Mitigation, and work they could not do at all before is Transformation. Those two are usually undercounted and carry the most weight in a budget conversation. If a workflow has no clear outcome, keep it in the report with the person's actual words, including "not sure." An honest receipt includes the parts nobody can explain yet, that gap is the most useful finding in the whole exercise. --- ## Build the report Write the payload to JSON and render: ```bash python scripts/build_report.py --data payload.json --out what-cowork-did-for-me.html ``` Payload shape is documented at the top of `build_report.py`, and `assets/sample_payload.json` is a complete working example. Required per workflow: `name`, `category`, `sessions`. Strongly recommended: `process`, `jtbd`, `pillar`, `frequency`, `outcome`. Save the report where the person can download it and present it to them. The report includes a live hourly-rate control that recalculates every dollar figure, and a Save as PDF button. ## After the report Offer one closing line they could actually use in a renewal or review conversation, built from their own words rather than generic phrasing. Point out the single largest workflow with no clear outcome, if there is one, as the thing worth watching next period. ## Notes - Time saved is an estimate of expert-equivalent time, not a measurement, and the report says so in its methodology section. If the person starts treating the figures as audited, restate that plainly. - The category bands in the taxonomy reference are directional defaults, not cited research. If the person's experience differs, adjust the band and rerun, that is a feature, not a workaround. - Keep the tone collaborative throughout. This helps someone build a case for their own work, it is not an audit of them.