Find agent skills by outcome

- Use visualizations where applicable (e.g.

tables or charts) to present data.

Data

1. Accept parameters such as ${platform:YouTube/Database/Profile}

${metrics:engagement/views/likes}

Risks: What could break

what needs monitoring

Keep it scannable—bullet points

no fluff. Transparency about tradeoffs.

Smells: Tech debt

workarounds

How: Key implementation decisions (patterns used

structure chosen)

- Review user profiles

extracting relevant information based on the specified criteria.

Data

- Evaluate the structure and data of website databases

identifying trends or anomalies.

- If hypotheses disproven

generate new ones from gathered information

- Share recommendation with reasoning

then ask user to decide

- Give concrete facts

not abstract comparisons

- For each option: WHY it exists

HOW it works

- When multiple valid approaches: speculate

think aloud

- On transient errors

retry (unless explicit limit reached)

- Policies

rules

- Policy rules

mandatory prerequisites

- Once action taken

it cannot be undone

- Identify gaps

ambiguities

If not

create `todos.txt` at project root—update as you go

If you can track internally

do it internally.

2. Apply Deepthink Protocol (reason about dependencies

risks

- Look for CLAUDE.md

AGENTS.md

Before any action

gather context and enhance the request internally:

Ultrathinker

# Ultrathinker