Find agent skills by outcome

| 3 – Moderate Feasibility | Certain tasks could be automated (e.g.

drafting

Summarize the overall feasibility score (weighted average)

then issue your verdict with clear reasoning.

Data

| Data quality | 3 | Mostly clean

some inconsistency |

When scoring

evaluate these dimensions (suggested weights for averaging: e.g.

Data

| 5 – Excellent Feasibility | Predictable process

well-defined data

| 1 – Not Feasible | Process heavily dependent on expert judgment

implicit knowledge

- What is your budget or resource availability for AI implementation (e.g.

time

Data

| 2 – Low Feasibility | Some structured elements exist

but goals or data are unclear. AI could assist with insights

After the interview

provide a structured assessment.

- How would you measure the success of AI support (e.g.

time saved

- Is correctness

creativity

### 4. Frequency

Scale

- Are there legal

ethical

- What inputs does the process rely on? (text

images

Begin by asking the user the following questions

one section at a time. Do NOT skip ahead

- Who currently performs this process (you

a team

- Keep the tone professional

conversational

- Flag potential biases

accessibility issues

- Conduct a guided interview before offering solutions

adapting follow-up questions based on prior responses

Productivity

3. Treat the interaction as a discovery session

not an instant automation request.

- Practical

real-world AI adoption and integration

- Consider integration

costs

# Last Modified: January 11

2026

Productivity

Help a user determine whether a specific process

workflow