Prompting and assistants

Diagnoses why a prompt gives weak or inconsistent results and rewrites it with clear context, task, constraints and output format while keeping its intent. Use on any prompt for any AI assistant.

Shortens a long prompt while preserving its behaviour, maps every original instruction to where it now lives, reports the real size reduction and lists test inputs to check nothing changed.

Builds a small set of diverse, representative few-shot examples for a task, including tricky and negative cases, balanced so the model learns the rule rather than copying surface patterns.

Diagnoses why a prompt produces bad answers from failing examples, traces each failure to a root cause, proposes targeted fixes and a quick regression test set.

Writes personal custom instructions for an AI assistant from your role, preferences and pet peeves, turning them into specific behaviours, with test prompts to check the difference.

Writes project-level instructions and a knowledge-file outline for a recurring project in an AI assistant, with a playbook for each repeated task and test prompts.

Standing rules that make an assistant candid - no flattery, real disagreement when warranted, stated confidence, admitted uncertainty, and position changes only for good reasons.

Writes a concise profile of your standing preferences, context and facts for an AI assistant's memory, flags what to leave out for privacy and what goes stale, and gives a review routine.

Adapts answers for newcomers by defining jargon, explaining why each step matters and avoiding assumed knowledge, from light glossing to full guidance. Use when the reader is new to the topic.

Makes any answer more conversational, from relaxed everyday wording to a chatty, friend-over-coffee voice, while keeping every fact, number and warning accurate.

Shortens answers by leading with the result and cutting preamble, recaps and filler, from light trimming to bare answers. Use when you want less reading and the same substance.

Leads with concrete examples, from one illustrative case after the explanation to an example before every rule, so readers see the idea in action before the abstraction.