Write formal board meeting minutes from an agenda, notes, transcript, or discussion summary. Use when asked to draft board minutes, governance minutes, meeting minutes for a board, or a formal record of decisions and actions. Produces structured board minutes with attendees, agenda items, resolutions, decisions, action register, and approval-ready wording.
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Build the storyline and slide structure for a board presentation. Use when asked to create a board deck, board presentation narrative, board meeting slides, or quarterly board update. Produces a complete slide-by-slide structure with narrative beats, talking points, and slide content guidance.
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Run the worst-case drill before an agent goes autonomous — the 'if this agent were fully hijacked right now, what's the damage' walk-through, the containment controls (caps, kill-switch, reversibility, isolation), and the recovery plan. Use when asked what's the worst my agent could do, run a blast-radius assessment, prepare for an agent going rogue, or am I ready to let this run unattended. Produces the worst-case walk-through, the containment controls, the reversibility audit, and the incident-recovery runbook.
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Decide when to buy a big-ticket item to get the best price — the sales cycles, model-refresh timing, and 'buy now vs wait' math for the specific thing you want. Use when asked when's the best time to buy [item], should I wait for a sale, is now a good time to buy, or when do [products] go on sale. Produces the typical discount calendar for that category, whether a new model/version is due (and if the current one will drop), a buy-now-vs-wait recommendation for your timeline, and price-tracking tactics — flagging that timing is a guide, not a guarantee.
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Decode an employment benefits package into what it's actually worth and where the fine print bites. Use when someone asks 'is this offer good', 'decode my benefits package', 'what does my equity actually mean', or 'what should I ask HR before signing'. Produces a benefit-by-benefit decode with real dollar values, ranked red flags (vesting cliffs, clawbacks, 'discretionary' bonuses, unlimited-PTO economics), and the questions to ask HR before signing.
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Check whether a raise, more hours, or a new job could cost you more in lost benefits than you gain — the 'benefits cliff' — before you accept it. Use when asked will a raise hurt my benefits, benefits cliff, if I make more will I lose my food stamps or medicaid, or should I take more hours. Produces a plain map of which benefits phase out at what income (and which cut off suddenly vs. taper), a rough read on whether a specific income change helps or hurts net, the ones with hard cliffs to watch (childcare, Medicaid, housing), the moves that soften a cliff, and where to get a real benefits screening. Not financial/benefits advice; points to a benefits counselor.
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Audit the beneficiary designations that quietly override wills — the account-by-account sweep, the life-event triggers that make them stale, and the coordination check against actual intentions. Use when asked check my beneficiaries, does my 401k go to my ex, do beneficiary forms beat a will, or what should I update after marriage/divorce/a birth. Produces the account sweep list, the stale-designation red flags, the intent-vs-paperwork comparison table, and the update checklist with the verify-in-writing step.
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Write a sincere, effective apology to a customer, group, or the public. Use when asked to write an apology, say sorry to a customer or community, make amends after a mistake, or respond to a complaint with an apology. Produces a genuine apology — acknowledgement, taking responsibility, empathy for the impact, the concrete fix and prevention, and an offer to make it right — in the right tone, without excuses or non-apologies.
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Set up and keep a job application tracker: one master CV, every tailored version, where each was sent, its status, next action and follow-up date, plus a weekly review of what is working. Use when asked to track my job applications, organise my job search, which CV did I send to which company, or what should I follow up on this week. Produces a tracker table (markdown or CSV) with one row per application, a version log linking each to its tailored CV, this week's actions, and a short weekly review of response rates by source.
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Write status updates people actually read — the traffic-light-plus-narrative format (state first, story second), the blockers-are-asks rule, and the skimmable structure that respects a reader with thirty seconds. Use when asked write my weekly update, format our team's status posts, nobody reads my updates, or what goes in a good async check-in. Produces the update format with a filled example, the blockers-as-asks discipline, and the reader-time contract.
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Produce a matched Chinese and English CV (中英文简历) from one set of facts: each version follows its own conventions rather than a literal translation, with names, titles, dates, education and company names rendered correctly in both. Use when asked for a Chinese and English resume, translate my CV into Chinese, 中英文简历, 英文简历, or apply to a foreign company in China or a Chinese company abroad. Produces the Chinese CV, the English CV, a consistency table proving the facts match, and a glossary of the terms chosen.
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Decide when and how your product and communications must (or should) label AI-generated content, and write the disclosure policy — surface-by-surface rules, exact label wording, and the review trigger for regulations like the EU AI Act's transparency obligations. Use when asked 'do we have to label AI content', 'write our AI disclosure policy', 'are we covered for the AI Act', or when marketing/support/product start shipping AI-generated output. Produces a disclosure policy with a per-surface matrix and ready-to-use label copy. Not legal advice.
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Check live air quality anywhere with zero API keys — Open-Meteo's air-quality API via curl, decoded from raw PM2.5 and AQI numbers into what they mean for going outside. Use when asked what's the air quality, is it safe to run outside, AQI in my city, or pollution levels right now. Produces the current AQI and pollutant levels, the plain-language health read with the standard bands, and the rerunnable command.
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Structure vague opportunities and unclear briefs into actionable one-page problem statements. Use when asked to clarify a vague brief, frame an undefined problem, make sense of an unclear opportunity, or when the user says 'we need to figure out what to do about X' or 'I've been asked to look into Y'. Produces a structured problem brief with reframed questions, scoped boundaries, and a minimum viable research plan.
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Prepare the conversations with aging parents that everyone postpones — the driving talk, the money talk, the care-options talk, the moving talk — each with an opener that doesn't ambush, a dignity-first script, rehearsal against realistic resistance, and the fallback when it goes badly. Use when someone says 'I need to talk to my dad about driving', 'my mum won't discuss her finances', 'we need to talk about care', or is dreading a visit for exactly this reason. Produces the conversation plan, a rehearsal, and the small-steps fallback. A preparation tool, not family therapy — and it says so when the situation needs more.
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Specify an autonomous or tool-using AI agent before building it. Use when asked to design an AI agent, define an agent's tools and guardrails, scope what an agent is allowed to do, or write an agent spec/PRD. Produces an agent spec — goal & scope, tools with permissions, the control loop, guardrails & approval gates, memory, escalation/handoff, evaluation, and failure handling.
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Simulate the acquirer's diligence team hunting for reasons to cut your price — their internal red-flags memo with a price-chip estimate per finding. Use when asked to red-team my company before a sale, how will an acquirer attack our valuation, pre-diligence audit, or what will DD find. Produces the acquirer's internal memo (revenue quality, key-person, tech debt, concentration, legal) and a debrief on which flags are fixable before a process.
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Analyse a finished A/B test and write the readout — the result, whether it's statistically and practically significant, what it means, and the ship/no-ship call. Use when asked to analyse experiment results, write an A/B test readout, interpret test data, or decide whether to ship a variant. Produces a clear verdict with the lift and confidence, segment cuts, the risks (peeking, novelty, sample), and a recommendation. Distinct from planning a test — this reads results.
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Design statistically rigorous A/B tests for product features, UI changes, onboarding flows, and pricing experiments. Use when asked to set up an experiment, design an A/B test, calculate sample size, or interpret test results. Produces a complete test plan with hypothesis, variant definitions, sample size, duration estimate, guardrail metrics, and a results interpretation guide.
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Make an AI agent or automation reliable enough to trust — the tests, checks, and guardrails that catch its failures before they reach anything real. Use when asked how do I test my AI agent, make my automation reliable, my agent works sometimes, or how do I trust an AI workflow in production. Produces a map of where the agent can fail (bad input, hallucination, wrong tool call, edge cases, silent errors), the checks that catch each (validation, evals on real cases, human-in-the-loop gates, monitoring), a right-sized reliability plan scaled to the stakes, and a rollout that earns trust incrementally.
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Use when asked to walk me through an annual report, teach me to read this 10-K, explain a company's accounts to a beginner, or tutor me on the financial statements in an uploaded report. Walks a beginner up a fixed six-rung ladder — statement map, balance sheet line by line, operating profit to free cash flow, five sector-appropriate ratios with healthy ranges, the sceptical read, then a reusable checklist and a five-question quiz. Produces a page-referenced tutorial in which every figure cites the page it came from and anything missing is marked 'not disclosed in this report'. Educational, not financial advice.
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Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes. Use when a CFO asks what the AI tools returned, when renewing AI contracts, when consolidating overlapping AI subscriptions, or to build the measurement plan before the next spend. Produces an ROI audit with per-tool verdicts (keep/consolidate/cut), the honest-measurement method behind each number, and a baseline plan for whatever can't be scored yet. To forecast ROI before an investment use roi-estimator; this skill measures what already happened.
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Design an evaluation plan for an LLM or AI feature before shipping it. Use when asked how to evaluate a prompt/model/agent, set up an eval harness, define quality metrics for an AI feature, or build a regression gate. Produces an eval plan — task definition, datasets, metrics & rubrics, baselines, automated + human evals, a pass bar, and a regression gate.
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Work through the first hours and days after a disaster — a fire, flood, storm, or evacuation — in the right order: safety and people first, then documenting for insurance and aid, then the immediate recovery steps, without missing the things that cost money or health later. Use when someone says 'my house flooded/burned', 'what do I do after the disaster', 'we just evacuated, now what', or 'the storm damaged everything'. Produces a triaged action plan (safety → document → claim → recover), the do-not-miss list, and where to get help. Not legal advice; routes to emergency services and official aid.
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