Prompt engineering
Writing, improving and testing prompts for any AI assistant.
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- Improve a prompt
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.
- Adapt a prompt for a reasoning model
Rewrites a prompt for reasoning-capable models by removing step-by-step micromanagement, stating goals, constraints and success criteria, and keeping the output format exact.
- Adapt a prompt for a small model
Rewrites a prompt for a small or fast model with one job per call, simpler steps, explicit formats and more examples, plus a test that shows whether quality holds against the original.
- AI literacy coach
AI literacy coach who teaches people to use assistants well and critically - what they are good at, how they fail, how to verify outputs and protect privacy. Use for learning to work with AI.
- Anonymise text before pasting it into an AI tool
Replaces names, clients, codenames and confidential figures in text with consistent stand-ins before you paste it into an assistant, with a restore key and a check for clues left behind.
- Audit a prompt for bias
Audits a prompt for biased framing, stereotyped examples, proxy attributes, exclusionary assumptions and unequal treatment across groups, then suggests neutral rewrites and paired tests.
- Build an AI output review checklist
Builds a checklist a team uses to review AI outputs before use, tiered by risk, covering facts, sources, numbers, tone, privacy, rights and sign-off. For teams adopting AI in daily work.
- Build a prompt from input and output examples
Reverse-engineers a reusable prompt from input and output example pairs, naming the implicit rules, format and edge cases, then dry-runs the prompt against the examples, including held-out ones.
- Build a test set for a prompt
Builds a hand-run test set for a prompt with happy, edge and negative inputs, expected behaviour and checkable pass criteria per case, and a scoring sheet to compare prompt versions side by side.
- Build a team prompt library
Designs a shared prompt library for a team - structure, naming, an entry template with variables, ownership, review and versioning - and drafts the first entries for the team's top use cases.
- Choose a model tier for a task
Picks a first-choice model tier and reasoning setting for a task from its difficulty, volume, latency, cost and risk, with signs to step up or down and a check sized to the stakes. No model names.
- Choose the right prompting technique for a task
Matches a real task to the prompting techniques that fit it - examples, decomposition, attached sources, step-by-step reasoning, structured output or a tool - explains why, and writes a first draft.
- Choose temperature and other generation settings
Picks temperature, top-p, maximum output length, stop sequences and seed for an API task, explains each choice and gives a quick repeat-run test for consistency versus variety.
- Compare AI assistants on your own task
Sets up a blind side-by-side test of two or three assistants on your real prompts, then grades the pasted outputs against your criteria and recommends which to use and when.
- Compress a prompt
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.
- Convert an SOP into a prompt
Converts a standard operating procedure into assistant or agent instructions with ordered steps, decision rules, checks, escalation triggers, a gap list and test scenarios traced to the SOP.
- Create few-shot examples
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.
- Design a prompt chain
Splits a complex task into a chain of focused prompts with defined inputs and outputs, checks between steps, failure handling and a test plan. Use when automating multi-step work with AI.
- Diagnose prompt failures
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.
- Fix a prompt that keeps breaking a rule
Finds why a prompt keeps breaking a length, format or banned-word rule and fixes it with better placement, positive phrasing, matching examples and an output check where needed.
- Harden a prompt against injection
Hardens a prompt or assistant against prompt injection from untrusted content with input separation, an instruction hierarchy, least-privilege actions, output limits and an attack test set.
- Learn prompting basics
Teaches prompting basics interactively on the learner's own tasks, one technique at a time, with before-and-after prompts, a short exercise and feedback. For beginners to AI assistants.
- Make a prompt work in several languages
Adapts a prompt so it answers in the user's language and local formats, keeps fixed terms untranslated, handles mixed-language input and comes with a test plan per language.
- Port a prompt to another model
Ports a working prompt to another model family or vendor, adjusting structure, examples, format instructions and call settings, with a parity test plan. For builders switching models.
- Practise spotting AI errors
Trains AI literacy with rounds of assistant-style answers containing planted errors, such as invented citations, wrong maths or outdated facts, and coaches the user to catch and verify them.
- Prompt engineer
Prompt engineer who writes clear, testable instructions, iterates against real examples and evals, and avoids model-specific tricks. Use for designing, debugging and maintaining prompts.
- Prompt iteration track
Improves a prompt in gated steps - define success, build test cases, run and grade, diagnose failures, revise, then compare versions on the same cases before adopting the change.
- Red-team a prompt
Tests a prompt or assistant setup against adversarial inputs - injection, edge cases, off-topic and harmful requests, data leaks - predicts failures and proposes fixes. For assistant builders.
- Reduce made-up answers from a prompt
Rewrites a prompt so answers stay grounded, using source-only answering, quote-then-answer, an explicit not-found reply, known-versus-inferred labels and checkable citations.
- Run prompt regression tests
Runs a prompt test set against the current and candidate prompt versions with the project's command, grades outputs with the stated checks and reports regressions, wins and flaky cases side by side.
- Run a prompting workshop for your team
Plans a 60 to 90 minute hands-on team workshop on using AI assistants, built on the team's own tasks, with timed exercises, before-and-after prompts, verification habits and data rules.
- Structure a prompt for prompt caching
Reorders a long prompt into a stable prefix and a variable tail so provider prompt caching hits, lists the code changes, and estimates the cost and latency saving from your traffic.
- Turn a chat into a reusable prompt
Turns a successful chat conversation into a reusable prompt with named variables, the rules learned from your corrections, an output format and a worked example. Use for tasks you repeat with AI.
- Write a batch processing prompt
Writes a prompt for processing many items consistently through an API or script, with a per-item output schema, stable labels, ID echo, error records and a QA sampling plan.
- Write a task brief for a browsing agent
Writes a task brief for a browsing or computer-use agent with a clear goal, allowed sites, choice criteria, stop-and-confirm points before purchases or submissions, and a result format.
- Write a roleplay character prompt
Writes a roleplay character prompt with personality, voice samples, knowledge limits, boundaries and consistency rules. For interactive fiction, language practice, training and games.
- Write a classification prompt
Writes a classification prompt with sharp label definitions, include and exclude rules, boundary cases, balanced examples and an abstain option, plus a plan to measure accuracy on labelled data.
- Write multi-turn test conversations for a chatbot
Writes multi-turn test scripts for a chatbot or custom assistant covering follow-ups, corrections, topic switches, long-chat drift and pushback after a refusal, with a pass check for each turn.
- Write a data analysis prompt
Writes a prompt for an assistant with code execution to analyse an uploaded CSV or spreadsheet correctly - inspect first, state assumptions, show code, reconcile totals, flag dirty data.
- Write a deep-research brief
Writes a brief for an AI deep-research run - precise question, scope, source rules, output format and how to judge the result - so a research agent investigates the right thing.
- Write an expert panel prompt
Writes a prompt that has an AI critique a plan from several distinct expert perspectives, with forced disagreement, evidence for each view, and a synthesis that keeps the unresolved conflicts.
- Write a system prompt for an internal HR or IT helpdesk bot
Writes the system prompt for an internal HR or IT policy assistant that answers from company policy with its name and date, refuses outside scope and hands off to a person.
- Write an image analysis prompt
Writes a reusable prompt for reading screenshots, charts, receipts, forms or photos with an AI that can see images - region by region, illegible parts marked, seen kept apart from inferred.
- Write an interview-first prompt
Writes a prompt that makes an assistant ask targeted questions one at a time before producing a document, plan or answer, with a question budget, a stop rule and a summary check.
- Write an LLM-as-judge prompt
Writes an LLM-as-judge grading prompt with a calibrated scale, anchored examples for each score, ordered criteria and a structured verdict, plus checks for common judge biases.
- Write a length-limited copy prompt
Writes a prompt that reliably produces copy within hard character or word limits - ads, SMS, meta descriptions, bios, form fields - using target ranges, counts, code checks and trimmed variants.
- Write a long document prompt
Writes a prompt for analysing long documents with document placement, metadata tags, quote-first answering, citations, a not-found rule and a chunking plan for documents that do not fit.
- Write a long-form generation prompt
Writes a prompt set for getting long documents such as reports, guides or manuals from an AI past output limits - outline first, section by section, continuity notes and a final consistency pass.
- Write a summary template for an AI meeting note-taker
Writes a custom summary template and instructions for an AI meeting note-taker with decisions, owners and dates as stated, open questions, and rules against inventing actions or attendees.
- Write prompts for an office suite assistant
Writes prompts for the AI assistant inside a word processor, spreadsheet, email or chat app that point to the right files, ranges and threads and ask for output you can check.
- Write a ranking prompt
Writes a prompt that scores and ranks a list of items such as leads, applications, ideas or tickets against weighted criteria, with evidence per score, tie rules and checks for order bias.
- Write a reliable maths prompt
Writes a prompt that gets correct numbers from an AI for quotes, budgets and conversions - code or calculator use, shown workings, units, rechecked totals and flagged estimates.
- Write a report template prompt
Writes a reusable prompt that turns raw notes into a fixed recurring report - weekly status, incident, site visit or shift handover - under exact headings, with missing inputs flagged, never filled.
- Write a research table prompt
Writes a prompt that fills a comparison matrix of vendors, tools or options criterion by criterion, with a source and date per cell and "unknown" instead of guessed values.
- Write sensitive-topic guidelines for an assistant
Writes the system prompt section that sets how an assistant handles medical, legal, financial and mental-health questions - scope, caveats, crisis routing and referrals - with tests.
- Write prompts for spreadsheet AI functions
Writes prompts for AI functions inside spreadsheet cells that classify, extract or rewrite each row consistently, with fixed outputs, blank handling, cell assembly and a spot-check plan.
- Write a structured output prompt
Writes a prompt that returns schema-valid JSON reliably, with a JSON Schema, field rules, examples, edge-case handling and a validate-and-retry plan. For extraction and app integrations.
- Write a summarization prompt
Writes a reusable summarization prompt for a recurring document type and reader, with keep and drop rules, length, structure, faithfulness rules for numbers and uncertainty, and a test plan.
- Write a synthetic customer persona prompt
Writes a prompt that simulates a target customer to give early feedback on ideas, copy or flows, grounded in supplied research, with clear caveats on what simulated feedback cannot tell you.
- Write a system prompt
Writes a system prompt for a custom assistant from its purpose, audience, boundaries and tone, with handling for missing information and off-topic requests, plus a set of test questions.
- Write a reusable task prompt
Writes a reusable prompt from a plain description of a task, with context, typed variables and defaults, constraints, an output format, an example and a rule to ask for missing inputs.
- Write instructions for a no-code agent with tools
Writes instructions for a no-code agent with tools or actions - when to call each one, what to confirm first, how to handle failures and when to stop - plus tool descriptions and test chats.
- Write a translation prompt
Writes a reusable AI translation prompt with audience, register, glossary, do-not-translate list, formatting and placeholder preservation, and a self-check for omissions and added meaning.
- Write a system prompt for a voice agent
Writes a system prompt for a voice assistant or phone agent with short spoken turns, confirmation of key details, recovery from mishearing and silence, tool use and a graceful handoff to a human.
Not: coding-agent operations (meta).