資料には具体的なスキルの内容や手順が記載されていないため、用途や得られる結果を特定できません。
- 用途を確認したいとき
- 入力や手順を確認したいとき
- 期待する結果を確認したいとき
広告やメールなど各チャネルの実績を売上や有望な商談など事業の指標で見直し、週次レポート、要因分析、次に試す施策をまとめます。
Weekly performance read across every channel we run: what worked, why, and what to make next, judged on the business's real number (store revenue, qualified pipeline, retained users), not platform claims. Use when: write my Monday report; how are my ads doing — which ad won?; are my ads actually making money (Meta says 4x ROAS but revenue is flat); why did sales drop this week; did the test win; is my tracking working; monthly numbers for the replan; anything on fire today. Not for acting on the recommendations (pausing, scaling, launching) — use run-paid-campaigns; not for replanning the budget — use plan-campaign.
実行スコア 未検証
インストール方法を見る広告、メール、SNSなど運用中のチャネルを横断して実績を読み解き、週次レポートにまとめます。プラットフォームが申告するROASなどだけで判断せず、店舗売上、有望な商談、継続ユーザーといった事業側の指標を照合します。どの広告や施策が成果につながったか、変化の理由、計測上の問題、次に作るものや試す内容を整理します。月次の数値確認や、依頼に応じた日次の異常確認にも対応します。
レポートは所定の形式で保存され、チャネルや広告ごとのスコアカード、過去の傾向、先週の提案の結果も記録します。売上など実測値、プラットフォーム上の申告値、推定値は区別して扱います。接続や参照データが不足する場合は、確認できた範囲を明示します。
週次のマーケティング報告を作るとき、広告が実際の売上に結びついているか見たいとき、売上低下や計測の不具合を調べたいときに向いています。テスト結果の判定や月次の振り返りにも使えます。
このスキルは読み取りと提案を行います。広告の停止・拡大、予算変更、キャンペーン実行は行いません。十分な売上やCRMデータがない場合、確認結果はプラットフォーム申告値中心になります。
この紹介文は、公開されている SKILL.md をもとに AI(OpenAI Codex)が作成しました。正確な仕様は下の原文を確認してください。
インストールする前に、エージェントに与えられる指示の中身を確認できます。
reports/performance/<YYYY-MM-DD>.md and shown in chat, the same shape every week (references/monday-report.md); run-paid-campaigns decides and acts on its recommendations.references/run-memory.md): the per-channel and per-ad scorecards with the trend since last run, each call with its owner, review date and test, and what happened to last week's calls — saved to the brand, so "what worked" and "what to make next" rest on weeks of history, not one week.references/monthly-and-pulse.md).marketing-guide skill (../marketing-guide/SKILL.md) §1–2 (connect, brand, brain read) before anything else; the job line is "read your results". This playbook offers local mode (marketing-guide §5): with no GooseWorks it reads through the marketer's connectors, else exports and screenshots, and keeps the contract, reports and run records in the local folder. A missing connection is never a blocker: say in one line what this read can and can't see, and go on.references/local-mode.md instead). Brain chapters: 18 "How we count results", 20 "Our plan" (targets, decisions, experiments), 22 "Everything we have made and run", 23 "What is working" (readouts, worn-out angles, lessons). Fallback path: brand_read sections summary, kit, products, learnings, onboarding, accounts, and knowledge_search ["learning"] for past results. Then gooseworks:campaign_read — live briefs (Economics, targets, Test plan, Measurement plan, Replan triggers, the change-log slug in Status); workspace (gooseworks:file_list / file_read): reports/performance/definitions.md, the latest dated report and its Decisions, ads/campaigns/<slug>/state.md (frontmatter meta_push_ids, health line, open recommendations) and the ### YYYY-MM-DD — <title> blocks of decisions.md (what was actually done — written by run-paid-campaigns and the server), make-static-ads' batch files ads/batches/<YYYY-MM-DD>-<slug>.md (creative id → angle, hook, test; picks), lifecycle/program.md (which flows exist), the newest research/competitors/watch/<YYYY-MM-DD>.md (line 2), and research-market's "What people are saying" section — in the newest research/market/<D>-read.md (mentions, sentiment, trends, risks; check the section's own window line before treating it as this week's, and read share of voice only if it is there).run-memory skill (../run-memory/SKILL.md) for this job (weekly performance read, monthly read or daily pulse; references/run-memory.md): the last record, plus up to four weekly records back for the scorecards and angle history; every earlier call checked against a source; run-paid-campaigns' newest run record for each campaign (its money moves and verdicts). No record → say it's the first read; this run's numbers become the baseline.references/measurement-contract.md §1. The type decides the referee, the ranking metric, the cadence (B2B under ~20 SQLs a month: weekly = leading indicators, pipeline monthly; services: monthly) and the inputs.references/measurement-contract.md §4 (minimum useful read first, history once, big exports in a hosted chat). Add what only this run knows: on the first run, the contract draft with defaults pre-filled (ask only the number and target, margin %, timezone — never technical settings), the roster to confirm, and which store, CRM, billing or analytics tool holds the referee unless the brain or a listed connector shows it (marketing-guide §3, "The marketer's own tools"; with none, that leg runs claims-only meanwhile); exports named in the last record's "Not checked" line, by name; the paid run's needs (references/run-memory.md § What the one input message also asks for). Missing items are "not checked this week"; a missing referee → claims-only mode (references/measurement-contract.md §5).GooseWorks reads (connected only): gooseworks:meta_read performance view (Goose ads only, trailing windows ranked by spend — to identify Goose ads and cross-check, not as the week's totals); gooseworks:social_account_list + gooseworks:social_analytics_get (the brand's TikTok/Instagram accounts — other platforms come from the marketer); gooseworks:ads_creative_read (statics' lower-case tags, e.g. angle:a-07, picked; the batch file is the fallback when tags are missing) and gooseworks:video_read (videos' angle and hook names; a video without them is unannotated; an older ads/videos/<project_id>.md note is read only if it exists).
Route first. "Anything on fire today?" → run Before you start 1–3, then only the pulse in references/monthly-and-pulse.md — no input message, no contract. "Monthly numbers / replan" (or the first Monday of the month) → add the customer-level store export to this week's one input message, run the weekly read, then the monthly read. Everything else → the weekly read below.
analyze-performance-intake skill (../analyze-performance-intake/SKILL.md). On a first run, save the contract (confirmed, or as "draft — awaiting confirmation" if the marketer sent exports without confirming) to definitions.md and register it as a brand document through the save-to-brain skill (../save-to-brain/SKILL.md) (versioned: supersede); re-check the roster against the briefs and state.md and propose an amendment when a new channel appears. Strip test/wholesale/staff orders and renewals; net refunds; align timezones; equal-lag comparison; de-duplicate Goose ads against the export by ad id; save the input summary; write the coverage line over the roster.analyze-performance-revenue-join skill (../analyze-performance-revenue-join/SKILL.md), references/revenue-join.md. The type's referee vs last week, the 4-week average and the same week last year (or "vs plan only" for a new brand); for DTC: MER (labelled DTC MER when retail exists), new-customer MER, nCAC, contribution after ads vs break-even; the overclaim ratio on like-for-like terms; marginal vs average; budget pacing vs the month. When platform and blended disagree: both stories at the same grain, a recommendation, the cheapest settling test.analyze-performance-diagnose skill (../analyze-performance-diagnose/SKILL.md), references/diagnosis.md. Plumbing first (breaks from the numbers, run-paid-campaigns' health line, and "measurement absent by design" with setup steps). Then, for every material move, the cause checklist with evidence, how sure, and ruled-out causes; light page/message match on the top winning and losing ads.analyze-performance-rank-and-read skill (../analyze-performance-rank-and-read/SKILL.md), references/creative-and-channels.md. Build the per-channel and per-ad scorecards against last run's rows (references/run-memory.md § Numbers). Angle → hook → format ranked by spend and judged on the type's business event (DTC: purchase CPA within the platform, claimed, capped at likely unless store new-customer orders moved with it); when only an upstream proxy exists (installs, leads, clicks), "cheap <event>, quality unknown" — no winner, no learning, "test" not "scale"; ads without a maker's angle annotation are "unannotated", never guessed from names. Then each rostered channel: email/SMS, organic, Google (+ wasted-spend terms), apps, local, B2B pipeline.analyze-performance-call-and-learn skill (../analyze-performance-call-and-learn/SKILL.md), references/tests-and-learnings.md. Ended tests called against the brief's criteria; last week's calls scored through run-memory's outcome check (a money move run-paid-campaigns made: its verdict, plus this playbook's store-joined truth check over the same window); "what worked" only what held 2+ runs or won a test, "what to make next" from the history — tiring winners first, nothing that already failed (references/run-memory.md); this week's recommendations with how sure and "would change if" (the decision and the action are run-paid-campaigns'); fired replan triggers; the "what to make next" list; at most ~3 proposed learnings (n floors apply), each showing what it would retire.write-report skill (../write-report/SKILL.md), in references/monday-report.md's shape (topic performance-read; brand copy reports/performance/<YYYY-MM-DD>.md, title Performance read — <Brand> — <YYYY-MM-DD>, tags [analyze-performance, performance-read], keep-history). Its §3 checks, plus: labels per section (truth / claimed / derived); no platform revenue as truth; every rostered channel present; every call says how sure. Its Decisions for you is the one decisions block: which story to run on (if two), which learnings to keep or strike, any contract amendment, any re-test.definitions.md; write the kept learnings through the save-learning skill (../save-learning/SKILL.md) (their words as the statement; one idea per learning; own superseded ones retired; say which landed). Nothing becomes a learning unless it appeared in a report the marketer saw. Measured readouts (ended tests called Win or Loss) are saved through save-learning's readout path, never from a scheduled run (references/run-memory.md § Experiment readouts).run-memory skill (../run-memory/SKILL.md): the record with the scorecards, the angle history line, this run's calls as recommendations (id, owner, review-by, how we'll know) and the outcomes of the last ones. Re-save it with the marketer's decisions when they reply. The daily pulse writes a pulse record (thresholds checked, breaks or "nothing").references/monthly-and-pulse.md, with its own monthly read record (channel scorecard over the month vs the last monthly record).Nothing here is irreversible: this playbook reads and recommends; it never moves money, changes campaigns or publishes. Its judgment points end at the marketer:
spend-gate skill (../spend-gate/SKILL.md)'s automation rule (created paused, switched on by the marketer); the offer is recorded in definitions.md so it isn't repeated. Create it by marketing-guide §3 Schedules. With GooseWorks (gooseworks:automation_upsert): the method goes in reports/performance/method/, the prompt is references/run-memory.md § Setting up the schedule. Local mode: the host-scheduler branch there. Either way: read and report only; never apply, publish or spend.gooseworks:file_write, re-read before writing; local mode: references/local-mode.md): reports/performance/<YYYY-MM-DD>.md (weekly — named for the Monday of the run week, kept when re-saved with Decisions), reports/performance/monthly/<YYYY-MM>.md, reports/performance/inputs/<YYYY-MM-DD>.md, reports/performance/definitions.md. The contract (versioned: supersede) and the monthly read (a period artifact, keep-history) are also registered as brand documents through the save-to-brain skill (../save-to-brain/SKILL.md).runs/analyze-performance/<job-slug>/<YYYY-MM-DD>.md through run-memory (imported; read by its own next run and plan-campaign's replan). Experiment readouts (kind 23 experiment_readout.*) and, on the marketer's yes, worn-out angles (worn_out_angle.*) through save-learning.[learning YYYY-MM-DD A-NN] so research-competitors can update its bank).On a brand with live spend and its store or CRM numbers provided, each rostered channel's winner, the why and the next-make are stated and grounded; platform revenue is never quoted as truth; learnings were written only from the marketer's words after they saw them. Without the referee it says plainly that it ran claims-only — the Done-when check needs the referee.
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資料には具体的なスキルの内容や手順が記載されていないため、用途や得られる結果を特定できません。
顧客の課題や商品情報、広告事例を調べ、根拠のある広告訴求と静止画・動画・コピー案にまとめます。動画案は実際の制作フォーマットとの相性も確認し、商品単位の角度集として整理します。
Google、Meta、LinkedInなどの広告実績を分析し、成果の出た広告や予算の無駄を特定します。停止・拡大・テスト案や、具体的な予算配分を提案します。
広告費と登録後の成果を照合し、質の高いリード獲得にかかった実コストを算出します。広告素材ごとに拡大・維持・調査・停止の判断材料を整理するスキルです。
Meta広告を始める前にブランド情報を調べ、予算や広告表現に関わる不明点だけを質問して準備を整えます。確認事項と仮定を記録し、ブランド情報とキャンペーン概要を作成します。
広告文や画像内の表現を配信先と商品カテゴリのルールに照らして確認し、直せる箇所を修正しながら、法務や人の判断が必要なリスクを広告ごとに整理します。