「ticket」の検索結果

Plan a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

日本語の概要は準備中です。原文の説明を表示しています。

Implement a piece of work based on a spec or set of tickets.

日本語の概要は準備中です。原文の説明を表示しています。

When the user has raw customer interview transcripts, survey responses, support tickets, or other qualitative data and needs to extract actionable insights.

日本語の概要は準備中です。原文の説明を表示しています。

FAQ identification from support tickets, step-by-step tutorial creation, screenshot/video script guidance, search optimization, and self-service deflection tracking.

日本語の概要は準備中です。原文の説明を表示しています。

Build a quarterly business review from a client folder -- reports, usage exports, support tickets, meeting notes, emails. Extracts delivered value with receipts, surfaces risks before the client does, and drafts the QBR narrative plus expansion asks. For agencies, consultancies, and CS teams.

日本語の概要は準備中です。原文の説明を表示しています。

Generates a comprehensive client health overview across all accounts. Reads CRM data, support tickets, usage metrics, billing, and engagement logs. Calculates health scores, trend direction, and RAG status per client. Outputs a sorted risk report with recommended actions.

日本語の概要は準備中です。原文の説明を表示しています。

Post-mortem analysis when a client churns. Takes client history, engagement data, support tickets, usage logs, and exit feedback to produce a comprehensive churn autopsy with root cause classification, timeline of decline, and preventive measures.

日本語の概要は準備中です。原文の説明を表示しています。

Turn a work-items.md file (produced by /plan-work-items) into Linear issues, one per slice, in a single target Linear team. Use when you want to publish work items as Linear issues, create implementation tickets to track in Linear, or push a broken-down plan into a Linear team. Requires a configured Linear MCP server and a target team. Reads the team's real workflow states, labels, Projects, and members and resolves every option against them before creating anything; defaults each issue to the team's initial state, unassigned, uncategorized, with no parent or Project unless you ask. Links within-file `Depends on` relationships as native Linear "blocked by" relations and annotates the source file so re-runs resume cleanly. Does not produce the work-items file itself — use plan-work-items first. Does not post to Jira — use work-items-to-jira. Does not post to GitHub — use work-items-to-issues.

日本語の概要は準備中です。原文の説明を表示しています。

Break a trusted implementation plan (or other provided context) into independently-grabbable, atomic work items, written to a single work-items.md file. Use when the user wants to convert a plan into work items, create implementation tickets or tasks, divide a plan into work units, or break the plan down into grabbable pieces. Do not use when there is no implementation plan yet or the plan is not yet trusted — use plan-implementation to produce the plan or iterative-plan-review to harden it first. Does not sequence work into demoable delivery phases — use plan-a-phased-build for that. Does not write code — use tdd to implement a work item.

日本語の概要は準備中です。原文の説明を表示しています。

Walks a person through code changes one step at a time in conversation, starting at the entry point and following the flow that changes, showing a small chunk per step and explaining it in plain language. Defaults to the current branch's changes, and walks the code from the perspective of any context provided instead — a file, directory, symbol, pull request, plan, or ticket. Use when someone wants to be walked through, taught, paced through, or shown around code or a branch step by step, or to learn how a change works before reviewing or extending it. Stops after every step and waits, so the learner sets the pace. Paces through code that already exists and builds nothing — to build new work while being paced through it, use pairing. Does not produce a written overview to read alone — use code-overview. Does not review code quality — use code-review. Does not diagnose bugs — use investigate.

日本語の概要は準備中です。原文の説明を表示しています。

Asana integration. Manage project management and ticketing data, records, and workflows. Use when the user wants to interact with Asana data.

日本語の概要は準備中です。原文の説明を表示しています。

Draft professional, empathetic customer-facing responses adapted to the situation, urgency, and channel. Use when responding to customer tickets, escalations, outage notifications, bug reports, feature requests, or any customer-facing communication.

日本語の概要は準備中です。原文の説明を表示しています。

Write and maintain knowledge base articles from resolved support issues. Use when a ticket has been resolved and the solution should be documented, when updating existing KB articles, or when creating how-to guides, troubleshooting docs, or FAQ entries.

日本語の概要は準備中です。原文の説明を表示しています。

End-to-end, phase-gated SDLC for AI coding agents: relentless design interview → reviewed spec → dependency-graphed task board → safe-wave TDD execution → verification → converge. Handles features, bugs, refactors, greenfield projects, planning breakdowns, and migrations. Triggers on "absolute work", "build this end-to-end", "plan and build", "break this into tasks", "grill me on this plan", "pick up this ticket", "run this migration".

日本語の概要は準備中です。原文の説明を表示しています。

Add fast, local, typed decisions to any project with Laya, an open-source non-generative decision model (pip install laya). It classifies, routes, scores and answers yes/no questions about a piece of text, returning calibrated probabilities in roughly 20-35 ms on a laptop GPU, with no LLM call and no data leaving the machine. Use this skill whenever the user wants to classify or route text, triage tickets or emails, detect spam, phishing, toxicity or intent, put a guardrail in front of an agent or LLM, score something against a rubric, or replace an LLM-based classifier to cut latency or cost. Also use it when they mention Laya, Jev, a "System 1 model", "typed decisions" or a "decision model", even if they never name Laya.

日本語の概要は準備中です。原文の説明を表示しています。

Implement the result of /to-spec and /to-tickets in code.

日本語の概要は準備中です。原文の説明を表示しています。

Plan a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

日本語の概要は準備中です。原文の説明を表示しています。

Implement a piece of work based on a spec or set of tickets.

日本語の概要は準備中です。原文の説明を表示しています。

Turn a vague bug report into a VERIFIED minimal reproduction and then a failing regression test, agent-driven end to end. Covers extracting the implicit repro from a thin report (env, build, steps, data), the reproduce-minimize-isolate-capture loop, git bisect to find the introducing commit, building a deterministic minimal repro (fixed seeds, frozen time, stubbed network), writing the failing regression test BEFORE the fix (red) and confirming the fix flips it green, and writing repro evidence back into the ticket. Distinguishes flaky-not-reproducible from environment-specific. Use when: "reproduce this bug," "minimal reproduction," "repro steps," "find the commit that broke it," "git bisect," "make the repro deterministic," "write a failing test for this bug," "regression test for a defect," "can't reproduce this bug." Not for: Classifying/deduplicating/severity-routing existing failures without reproducing them — that is ai-bug-triage. Generating tests from specs rather than from a defect — that is ai-test-generation. Related: ai-bug-triage, ai-test-generation, test-reliability, systematic-debugging, qa-project-context.

日本語の概要は準備中です。原文の説明を表示しています。

Master the AI tools that transform customer support from cost center to competitive advantage. Automate routine queries, empower agents, and delight customers at scale. Use when "customer support, helpdesk, ticketing system, chatbot, knowledge base, support automation, CSAT, customer service, support, helpdesk, chatbot, knowledge-base, customer-service, automation" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Drive one ticketed effort through parallel implementation, independent review, serial integration, and one open pull request.

日本語の概要は準備中です。原文の説明を表示しています。

Implement a piece of work based on a spec or set of tickets.

日本語の概要は準備中です。原文の説明を表示しています。

Plan a huge chunk of work — more than one agent session can hold — as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

日本語の概要は準備中です。原文の説明を表示しています。

When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," or "find out why customers churn/convert/buy." Use for both analyzing existing research assets AND gathering new research from online sources. For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.

日本語の概要は準備中です。原文の説明を表示しています。