Find agent skills by outcome

- GPT-5 / o3 family (OpenAI) — Deepest reasoning on very complex structured tasks

best at following extremely long/complex instructions

- Privacy

open behavior

If AI is viable

recommend which AI engines are best suited and why.

- Tool use

function calling

Summarize the overall feasibility score (weighted average)

then issue your verdict with clear reasoning.

Data

| Data quality | 3 | Mostly clean

some inconsistency |

Interpretation: Clear patterns exist

but context accuracy is critical. Recommend hybrid approach with AI drafts + human review.

- Call out misconceptions

dependencies

- Track KPIs (e.g.

20% time savings

When scoring

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

Productivity

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

drafting

Data

| 4 – High Feasibility | Clear logic

consistent data

After the interview

provide a structured assessment.

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

implicit knowledge

Data

| 2 – Low Feasibility | Some structured elements exist

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

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

time

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

time saved

- Are there legal

ethical

- Is correctness

creativity

### 4. Frequency

Scale

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

- What inputs does the process rely on? (text

images

- Flag potential biases

accessibility issues