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Claude Skills by mohitagw15856
github.com/mohitagw158562,747 skills66 installs2,935 views
- User Research SynthesisAnaliza y sintetiza hallazgos de investigación de usuarios en insights estructurados y accionables. Úsalo cuando te proporcionen datos de investigación de usuarios, transcripciones de entrevistas, resultados de encuestas o feedback de usuarios que necesiten ser analizados y resumidos. Produce una síntesis temática con datos de prevalencia, citas de apoyo, análisis de puntos de dolor, priorización de solicitudes de funcionalidades y próximos pasos recomendados. Para transcripciones de entrevis...Votes: 0GitHub stars: 1,330
- User Story WriterEscribir historias de usuario bien estructuradas con criterios de aceptación y casos extremos. Úsalo cuando te pidan escribir historias de usuario, crear tickets a partir de un resumen de características, convertir un PRD en historias o redactar criterios de aceptación. Produce historias listas para estimar en formato estándar con criterios de aceptación claros, casos extremos y definición de hecho.Votes: 0GitHub stars: 1,330
- Writing Great SkillsCrea un Agent Skill (SKILL.md) de alta calidad que la IA dispare y ejecute de forma fiable — frontmatter sólido, descripción incisiva con frases de activación, contrato de salida claro, controles de calidad y anti-patrones. Úsalo cuando te pidan escribir un skill, crear un SKILL.md, mejorar un skill, revisar un skill por calidad o contribuir a una librería de skills. Produce un SKILL.md completo que pase SkillCheck más una breve justificación de las decisiones clave.Votes: 0GitHub stars: 1,330
- Example Internal SkillAn example private skill — replace me. Use when demonstrating that org-private skills load, override, and stay inside your network. Produces this description in /v1/skills with source:private.Votes: 0GitHub stars: 1,330
- Agent Hiring PanelSummarise what Agent Hiring Panel does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Agent SeveranceSummarise what Agent Severance does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Ai Disclosure PolicySummarise what Ai Disclosure Policy does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Api For YourselfSummarise what Api For Yourself does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Clone BriefSummarise what Clone Brief does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Context BankruptcySummarise what Context Bankruptcy does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Deepfake DrillSummarise what Deepfake Drill does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- The Org SimulatorSummarise what The Org Simulator does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- The Time CapsuleSummarise what The Time Capsule does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- The UnderstudySummarise what The Understudy does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Accessible Travel PlannerSummarise what Accessible Travel Planner does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Accommodation RequestSummarise what Accommodation Request does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Disability Benefit AppealSummarise what Disability Benefit Appeal does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Disability Disclosure DecisionSummarise what Disability Disclosure Decision does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Venue Access CheckSummarise what Venue Access Check does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Cash Flow ForecastBuild a short-term (13-week) cash flow forecast to see if you can cover what's due. Use when asked to build a cash flow forecast, a 13-week cash flow, a cash projection, or to plan around a cash crunch. Produces a week-by-week forecast structure — opening cash, expected inflows, scheduled outflows, net movement, and closing/low-point — with the formulas and a worked example, plus the levers if cash goes tight. Not financial advice.Votes: 0GitHub stars: 1,330
- Collections EmailWrite a polite-but-firm payment-reminder / collections email sequence for overdue invoices. Use when asked to write a collections email, a payment reminder, a dunning sequence, or to chase an overdue invoice. Produces a staged sequence — gentle pre-due nudge through escalating overdue reminders to a final notice — that stays professional, keeps the relationship intact, and makes paying easy. Not legal advice.Votes: 0GitHub stars: 1,330
- Expense PolicyWrite a clear company expense & reimbursement policy. Use when asked to write an expense policy, a reimbursement policy, a travel & expense (T&E) policy, or spending guidelines. Produces a practical policy — what's covered, limits by category, the approval and submission process, timelines, and what's not reimbursable — that's fair, easy to follow, and reduces finance back-and-forth. Not tax/legal advice.Votes: 0GitHub stars: 1,330
- Financial Statement ExplainerExplain a financial statement (P&L, balance sheet, or cash flow) in plain English. Use when asked to explain a P&L / income statement, a balance sheet, a cash flow statement, or to make financials understandable to a non-finance reader. Produces a plain-language walkthrough — what each section means, the line items that matter, the key ratios, and the story the numbers tell — so a non-accountant can read and act on it. Not financial advice.Votes: 0GitHub stars: 1,330
- Invoice GeneratorCreate a professional, complete invoice for a client or customer. Use when asked to write an invoice, create a bill, draft a freelance/contractor invoice, or set up an invoice template. Produces a clear invoice — your and the client's details, a unique number, line items with quantities/rates, subtotal/tax/total, payment terms and methods, and due date — ready to send and easy to pay. Not tax/legal advice.Votes: 0GitHub stars: 1,330
- Skill FusionFuse two skills from this library into one hybrid brief for a task that sits between them — the meta-skill. Use when a task straddles two skills (a PRD that's also a pitch; a postmortem that must double as a board update) and running them separately would produce two documents where one is needed. Produces the fused operating brief: combined structure, merged quality bar, precedence rules for where the parents disagree, and the fused output itself if input was provided.Votes: 0GitHub stars: 1,330
- Agent Era PricingRedesign seat-based pricing for the agent era — when one human runs ten agents, per-seat models collapse. Use when agents are eroding seat counts, when asked to migrate to usage- or outcome-based pricing, to price an agent/API tier, or to defend revenue as customers automate their own usage. Produces a pricing migration plan: the new value metric, fences, agent-tier design, cannibalisation math, and a phased migration for existing customers. For general pricing and packaging strategy use pric...Votes: 0GitHub stars: 1,330
- Agent Readiness AuditAudit whether AI agents can actually use your product — docs, APIs, onboarding, errors, and discoverability, evaluated from a non-human user's perspective. Use when asked if a product is agent-ready, to audit a site or API for AI usability, to prepare for agentic traffic, or when agents keep failing against your product. Produces a scored readiness report with per-surface findings and a prioritised fix list. For optimising a single article for AI citation use aeo-optimizer; for designing the ...Votes: 0GitHub stars: 1,330
- Human In The Loop DesignDesign the human approval surface for an agent system — which actions gate, how approvals batch without becoming rubber stamps, and what the audit trail must hold. Use when asked to add human oversight to an agent, design approval workflows for AI actions, decide what an agent may do autonomously, or fix approval fatigue in an existing loop. Produces an action-tier policy, approval UX spec, escalation rules, and audit-trail requirements. For specifying the whole agent use agent-spec; for the ...Votes: 0GitHub stars: 1,330
- Mcp Server SpecDesign an MCP server for a product — the tool surface, auth model, and safety boundaries that make it genuinely usable by AI agents. Use when asked to spec an MCP server, expose a product to agents, design tools for Claude or other MCP clients, or review why an existing MCP server performs badly. Produces a complete server spec: a small task-shaped toolset with agent-tested descriptions, auth and scoping decisions, error design, and an explicit not-exposed list.Votes: 0GitHub stars: 1,330
- Voice Agent DesignDesign a voice AI agent for phone or in-app conversations — call flows, interruption handling, escalation to humans, and the metrics that catch a bad voice experience. Use when asked to design a voice agent, automate a phone line, spec an IVR replacement, or review why callers hate an existing voice bot. Produces a voice agent spec: persona and disclosure policy, conversation architecture, barge-in and repair behaviour, human-handoff rules, and a launch scorecard.Votes: 0GitHub stars: 1,330
- Agent Design ReviewReview an LLM agent design and find where it will be unreliable, expensive, or unsafe. Use when asked to review an agent architecture, critique a multi-step/tool-using agent, debug an agent that loops or goes off-task, or harden an agent before launch. Produces a structured review — task fit, control flow, tools, memory/context, failure handling, cost, and safety — with prioritised findings and fixes.Votes: 0GitHub stars: 1,330
- Agent Incident PostmortemRun a blameless postmortem for an incident caused by an AI agent or LLM feature — hallucinated facts shipped to users, runaway tool use, prompt injection, cost blowouts, or wrong actions taken autonomously. Use when asked to write up an AI incident, analyse why an agent did something wrong, or produce corrective actions after an LLM failure. Produces a structured postmortem with trace reconstruction, a root-cause layer analysis, and corrective actions including a permanent regression case. Fo...Votes: 0GitHub stars: 1,330
- Agent Observability SpecSpecify the tracing, metrics, and alerting for an AI agent or LLM feature in production. Use when asked what to log for an LLM app, design agent tracing or spans, define quality and cost monitors, or answer 'how do we know if the agent is misbehaving?'. Produces an observability spec with a trace schema, metric definitions with owners and alert thresholds, sampling and retention policy, and a privacy note for logged content.Votes: 0GitHub stars: 1,330
- Ai Eval PlanDesign 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.Votes: 0GitHub stars: 1,330
- Context Engineering ReviewReview what an LLM feature or agent actually puts in its context window — and find what's bloating, missing, or fighting itself. Use when asked to review a system prompt and context assembly, cut token usage without losing quality, debug an agent that ignores instructions, or audit how retrieval results, history, and tool definitions are packed into the window. Produces a context inventory with a keep/cut/restructure verdict per component, ordering and caching fixes, and a token budget. For w...Votes: 0GitHub stars: 1,330
- Llm Cost Latency BudgetModel the cost and latency of an LLM feature before it ships and surprises the bill. Use when asked to estimate LLM API costs, set a latency/token budget, decide which model tier to use, or bring down the cost of an AI feature. Produces a cost & latency budget — token math per request, monthly cost projection, model tiering, caching/streaming levers, p95 latency targets, and a guardrail/alert plan.Votes: 0GitHub stars: 1,330
- Model Migration PlanPlan the migration of an LLM feature from one model to another without breaking production. Use when a model is being deprecated, a newer model looks better or cheaper, or when asked how to upgrade models safely, run shadow traffic, or set rollback criteria for a model change. Produces a phased migration plan with eval gates, shadow/canary stages, prompt-adaptation notes, and rollback triggers. For choosing which model in the first place use model-selection-advisor.Votes: 0GitHub stars: 1,330
- Prompt Regression SuiteDesign a regression test suite that catches an LLM feature getting worse when the prompt, model, or context changes. Use when asked to stop prompt changes breaking production, set up golden tests or CI gates for an LLM feature, or test a model/prompt upgrade before shipping it. Produces a golden case set, per-case pass criteria, CI gate thresholds, and a triage protocol for failures. For designing first-time evaluation of a new feature use ai-eval-plan instead.Votes: 0GitHub stars: 1,330
- Aging Parent TalksSummarise what Aging Parent Talks does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Sibling Care SummitSummarise what Sibling Care Summit does in one line. Use when asked to [trigger phrases the user would say]. Produces [the concrete artifact].Votes: 0GitHub stars: 1,330
- Ai Agent ReliabilityMake 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, mo...Votes: 0GitHub stars: 1,330
- Ai Context PrimerBuild the context an AI needs to do a task well — the background, constraints, examples, and format it can't guess — so you get a great result on the first try instead of a generic one you have to keep correcting. Use when asked why does AI give me generic answers, how do I give AI better context, my AI results are mediocre, or how do I get it right the first time. Produces the specific context this task needs (who/what/constraints/examples/format), a reusable primer you can paste ahead of th...Votes: 0GitHub stars: 1,330
- Ai Output VerifierCheck AI output before you trust or use it — where it's likely wrong, what to verify, and how to catch confident-sounding errors. Use when asked can I trust this AI answer, how do I verify what AI told me, fact-check this AI output, or is this AI response reliable. Produces a risk read on the specific output (the claims most likely to be wrong or made up), the parts that need independent verification vs the parts that are low-risk, how to actually verify each, the tells of AI hallucination an...Votes: 0GitHub stars: 1,330
- Ai Tool PickerFigure out which AI tool actually fits the task in front of you — chatbot, coding assistant, image model, agent, or none — instead of forcing one tool onto everything. Use when asked which AI tool should I use for, what's the best AI for, do I even need AI for this, or should I use ChatGPT or something else. Produces a match between your task and the right kind of AI tool (with why), the trade-offs that matter for your case, when the answer is a non-AI tool or plain human effort, and how to t...Votes: 0GitHub stars: 1,330
- Ai Workflow DesignerDesign an AI-assisted workflow for a recurring task — which steps to hand to AI, which to keep human, and how they connect — so you get leverage without losing quality or control. Use when asked how do I use AI for [process], automate this with AI, design an AI workflow, or where does AI fit in my process. Produces a map of the task's steps split into AI-does / human-does / human-checks, the right tool/prompt for each AI step, the hand-offs and review points, the failure modes to guard agains...Votes: 0GitHub stars: 1,330
- Claude Project SetupSet up a repo or project so an AI coding agent works well in it — the CLAUDE.md, the context, the guardrails, and the conventions the agent needs to be useful instead of lost. Use when asked how do I set up CLAUDE.md, configure my repo for Claude Code, my AI agent keeps getting my project wrong, or onboard an AI agent to my codebase. Produces a structured CLAUDE.md/project-context file (architecture, conventions, commands, do-nots), the right level of detail (enough to orient, not a novel), t...Votes: 0GitHub stars: 1,330
- Delegate To AiDecide what in your workload to hand to AI and what to keep yourself — like managing a fast, capable, but unreliable new hire — so you get leverage without offloading the things that need you. Use when asked what should I delegate to AI, what can AI take off my plate, where should I use AI in my work, or what should I keep doing myself. Produces a sort of your tasks into delegate-fully / delegate-with-review / keep-human, the reasoning behind each line, how to brief the AI on the delegated on...Votes: 0GitHub stars: 1,330
- Get More From AiLevel up how you actually use AI — from basic one-shot questions to the techniques that get dramatically better results — matched to what you already do. Use when asked how do I get better at using AI, how do power users use AI, I feel like I'm using AI at 10%, or teach me to use AI better. Produces an honest read of how you use AI now, the two or three highest-leverage techniques to add next (giving context, iterating, showing examples, breaking down tasks, verifying), a concrete before/afte...Votes: 0GitHub stars: 1,330
- Memory File MaintenanceKeep your AI memory/context file (MEMORY.md, CLAUDE.md, custom instructions) healthy over time — pruning the stale, adding the new, and keeping it sharp so your AI keeps getting you right. Use when asked review my memory file, my AI context is outdated, clean up my CLAUDE.md, or maintain my AI instructions. Produces a review of your existing memory/instructions file (what's stale, contradictory, bloated, or missing), edits to prune and sharpen it, additions from recent patterns worth remember...Votes: 0GitHub stars: 1,330
- Prompt DebuggingFigure out why a prompt isn't working and fix it — diagnose the actual failure (ambiguity, missing context, wrong format, conflicting instructions) instead of randomly rewording. Use when asked why isn't my prompt working, the AI keeps ignoring my instructions, my prompt gives inconsistent results, or how do I fix this prompt. Produces a diagnosis of the specific failure mode, the targeted fix for it (not a vibes rewrite), a corrected prompt, a check that it generalizes rather than fixing one...Votes: 0GitHub stars: 1,330