retro
無料Explicit retrospective of a coding session with evidence-backed suggestions for future work.
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。
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概要と使いどころ
Explicit retrospective of a coding session with evidence-backed suggestions for future work.
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。
Analyze pi (coding-agent) session JSONL and ego-benchmark-harness run artifacts to explain slow or failed individual tasks, compare execution-path differences between agents or browser tools, and count tool calls and error types. Use this skill whenever users ask to analyze a pi session, explain why a task was slow or failed, compare two runs, investigate an error, locate the session corresponding to tasks.jsonl, inspect an agent execution path, count tool calls, analyze a run ID, or perform any forensic or retrospective analysis of JSONL under ~/.pi/agent/sessions/ or agent-home/.pi/agent/sessions/.
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-launch review of a shipped PRD against the brief's success metrics. Did we move the metric? What did the data actually show? Which assumptions held, which broke? Which accepted-gap decisions resolved (confirmed vs. invalidated)? What would we do differently? Triggers on "outcome review", "did it work", "post-launch review", "did we move the metric", "retro the feature", "was it worth it". Produces a Confluence outcome-review page and updates the brief + linked decisions.
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。
Drafts a blameless incident postmortem (summary, impact, timeline, detection and response, contributing factors as candidates for review, action items) from an incident channel export, ticket notes and any alert or change records, with UNKNOWN for every fact the inputs do not contain. Never assigns blame, names a root cause or re-rates severity. Use when the user asks to "write the postmortem for this incident", "build the incident timeline from the chat export", "draft the post-incident review" or "turn this ticket and channel log into an incident report". Do not use for a knowledge article from the resolved ticket, use knowledge-article-drafter instead; for project retrospectives, use lessons-learned-synthesis; for data-breach impact and notification questions, use data-incident-impact-brief. Drafts for human review; never approves, authorises or signs off.
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。
Synthesises a batch of customer feedback (survey answers, reviews, ticket and chat comments) into a DRAFT themed report: coded themes with record counts and shares, anonymised verbatim quotes cited to record codes, contradictions and unverified claims, and the follow-up questions to answer next. Produces no sentiment score or percentage positive as fact; ratings appear only as distributions with n. Use when the user asks to "theme this feedback", "what are customers saying", "summarise these survey answers", "analyse these reviews", "find the top complaints in these comments" or "code this voice of the customer data". Do not use for exit interviews, use exit-interview-synthesis instead; for sorting a live queue and drafting replies, use ticket-triage-pack; for project retrospectives, use lessons-learned-synthesis. Drafts for human review; never approves, authorises or signs off.
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。
Run a retrospective for an abandoned agent session (untouched for over 24 hours, never closed with a retro): rebuild context cold from the transcript, list what was built, sort Keep/Drop/Try and file the durable parts. Use from a nightly routine or on demand. Triggers: /retro-lost, retro for an abandoned session.
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。
Use when the user asks to "run a launch retro / post-mortem", "compare launch results vs targets by channel", or "decide what to keep or kill for the next launch"; produces a structured D1/W1/M1 retrospective — a per-channel actual-vs-target table (UTM-attributed own analytics as the truth column, platform self-reported numbers as reference, every figure labeled Measured / User-provided / Estimated), a 5-Whys chain on the single largest miss, keep / kill / change decisions per channel, 3-5 actionable learnings for the next launch, and an outcome snapshot submitted to the launch registry. Not for return math (CPA / ROI) — use roi-calculator; not for the stakeholder-facing report writeup — use report-generator; not for a metric deep-dive — use performance-analyzer. 发布复盘/渠道归因/5-Whys/keep-kill
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。
Use when working with Allma — allma incident management, collaboration workflows, post-incident learning, and channel orchestration. Covers incident creation via Slack, timeline tracking, stakeholder communication, automated workflows, and retrospective analysis. Use when managing active incidents, reviewing post-incident learnings, or analyzing incident patterns in Allma.
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。
Use when acting as the orchestrator agent that drives Syntropic137 - running the dogfood loop, deciding what to dispatch next, landing agent PRs, deploying a beta, triaging failed executions, or keeping the scratchpad, paper cuts and retrospectives current. Trigger phrases include "orchestrator tick", "keep the loop running", "what should we dispatch next", "land these PRs", "why are PRs stacking up", "deploy the next beta", "pit stop", "the run failed, what now", "write the retro", "is the system helping", "scale quality", "learning loop for the orchestrator". Do NOT use for deciding whether one task belongs in a workspace or locally (see `dogfooding`), for turning one incident into an eval case (see `learning-loop`), for designing a workflow A/B experiment (see `workflow-experimentation`), or for release-branch and version-bump mechanics (see `devops`).
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。
GameDay / FIS 実験の振り返りを行う。「振り返りして」「実験の結果をまとめて」「障害の影響を見せて」「ドリフト検出して」「講評して」など、実験の前後比較・影響分析・講評作成の全てで必ず使う。実験の「前」から使うスキルであることに注意 — ベースライン取得 (実験前) → 観測 (実験中) → 3 視点分析と KPT 講評の gameday.json への書き込み (実験後) までを一連で扱う。cdk drift / CloudFormation ドリフト検出、Synthetics canary の結果確認、CloudWatch メトリクスの前後比較が絡む作業も該当する。
Conduct a retrospective on a coding session.
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。
Apply continuous improvement principles to iteratively enhance processes, code quality, team practices, and system performance through small, incremental changes. Use when improving development processes, optimizing workflows, reducing waste, enhancing code quality over time, implementing retrospective learnings, or fostering a culture of continuous improvement.
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。
Evaluate learning progress, identify blockers, and adjust the learning plan
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。
Route communication modes, learning workflows, retrospectives, output discipline, and perspective shifts to focused productivity skills.
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。
Capture the "why" behind technical choices to prevent architectural drift. Load when the user makes a major technical decision, chooses a library/framework, defines a system boundary, or changes a core architectural pattern. Also triggers on "record a decision", "write an ADR", "why did we do this", "document this architectural choice", or "architectural decision record". Supports `SYNTHESIS=true` mode for retrospective ADR backfill from observed repo state — used by `retroactive-project-setup` and any future backfill skill. Essential for long-term project maintainability and agent alignment.
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。
Run a structured retrospective after development-phase runs of your product's agents — interview the owner in plain language about what went well and poorly, draft ranked improvement hypotheses, then design and run small n=1/n=2 experiments with pre-declared success criteria, guardrails, stop conditions, and a cost/ROI kill-switch. Load when the user says how did that run go, retro this run, the agent output was bad, what should we improve, draft hypotheses, run a small experiment, or after repeated dev runs of an agentic system produce uneven quality. Priority: output quality over performance over cost, each with diminishing-returns stops. NOT a product A/B test (experimentation), NOT coding-agent harness repair (harness-evolution), NOT production-scale learning (runtime-learning-loop).
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。
Complete OKR & Strategy Execution system — from company vision to weekly execution. Covers goal hierarchy, OKR writing methodology, scoring rubrics, alignment cascading, KPI dashboards, review cadences, team accountability, and quarterly planning rituals. Use when setting goals, running planning cycles, tracking OKRs, building KPI dashboards, running retrospectives, or aligning team work to strategy. Trigger on: "OKR", "objectives", "key results", "goal setting", "quarterly planning", "KPIs", "strategy execution", "annual planning", "team goals", "alignment", "review cadence", "what should we focus on", "prioritize", "goal tracking", "north star metric".
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。