Find agent skills by outcome

- Generate a simple

practical starter prompt

- Lightweight/chat-only models (older 7B–13B models

mini variants) — usually lack depth/context/tool reliability

- Keep it minimal and adaptable

including placeholders for iteration or error handling

- Instead

suggest non-AI or hybrid alternatives (e.g.

- Mistral Large 2 / Devstral — Very strong price/performance

fast

- Gemini 2.5 Pro / Flash (Google) — Outstanding multimodal (especially video/document understanding)

very large context windows

- Claude 4 Opus/Sonnet (Anthropic) — Exceptional long-form reasoning

writing quality

Current Best-in-Class Ranking (January 2026 – general guidance

always tailor to the process):

- Privacy

open behavior

- Tool use

function calling

- Track KPIs (e.g.

20% time savings

- Call out misconceptions

dependencies

If AI is viable

recommend which AI engines are best suited and why.

Summarize the overall feasibility score (weighted average)

then issue your verdict with clear reasoning.

Interpretation: Clear patterns exist

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

When scoring

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

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

time saved

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

implicit knowledge

After the interview

provide a structured assessment.

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

time

- Are there legal

ethical

### 4. Frequency

Scale

- What inputs does the process rely on? (text

images

- Who currently performs this process (you

a team