'subagent' 검색 결과

Execute implementation plan by dispatching fresh subagent for each task, with code review between tasks

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Execute plans via autonomous agents with two-stage review per task. Use for complex implementations requiring quality gates.

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Agent Skillのusability testを行うスキル。 下位tierのmodelのsubagentに、検証したいskillだけを頼りにゴールを与え、手を貸さずに観察し、終了後にインタビューとtranscriptの監査で判断の根拠を確かめる。 ユーザーが「skillのusability testをして」「skillをE2Eテストして」「手順書だけで完遂できるか試して」と言った時に使用する。 手順の追加や組み替え、新しいコマンドの組み込み、ガイドラインの判断基準の変更のように、skillのワークフロー構成や判断基準に影響する変更をした後に、実行をユーザーに提案する。

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リポジトリのセキュリティ調査を領域ごとに進める。同じサービスを構成する複数のリポジトリを束ねて調査できる。 このsessionは調査を指揮し、領域ごとに起動したsubagentが調査してレポートを出力する。 レポートの問題のトリアージと、問題の自動修正、問題を直すpull requestの状態の同期も指揮する。 複数sessionにまたがる長期作業を想定し、実行するたびに現状を確認して続きの作業を行う。 ユーザーが手動で起動する。

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セキュリティ調査で検出された問題を1つ修正し、pull requestをready for reviewまで仕上げる。 codepatrol skillが起動したsubagentが実行する。ユーザーが直接呼び出す事は想定していない。

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セキュリティ調査のレポートの問題を、どのtierの開発者なら修正できるかで分類し、トリアージページを作る。 codepatrol skillが起動したsubagentが実行する。ユーザーが直接呼び出す事は想定していない。

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リポジトリの1つの領域をセキュリティ観点で調査し、Codexの批判的レビューを経てレポートを出力する。 codepatrol skillが起動したsubagentが実行する。ユーザーが直接呼び出す事は想定していない。

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セキュリティ調査に使う調査対象リストと観点リストを、リポジトリのコードを読んで生成・更新する。 codepatrol skillが起動したsubagentが実行する。ユーザーが直接呼び出す事は想定していない。

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セキュリティ調査で検出された問題を直すpull requestの状態を、トリアージページと調査レポートに反映する。 codepatrol skillが起動したsubagentが実行する。ユーザーが直接呼び出す事は想定していない。

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本番に出る前の修正が積まれたrelease pull requestに、デプロイの前後に人間がやる事をまとめたコメントを投稿・更新する。 codepatrol skillが起動したsubagentが実行する。ユーザーが直接呼び出す事は想定していない。

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Pitfalls, examples, and edge cases for workers executing a Surogates subagent task. Loaded automatically when the dispatcher spawns a session bound to a Task (Session.task_id is set).

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Decomposition playbook and anti-temptation rules for an orchestrator agent that routes work through the Surogates subagent task layer. Pair this skill with an AgentDef whose tool filter strips the implementation tools (terminal, file, web, code) — that's how 'don't do the work yourself' is enforced structurally, not just behaviorally.

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Use when receiving code review feedback (especially if unclear or technically questionable), when completing tasks or major features requiring review before proceeding, or before making any completion/success claims. Covers three practices - receiving feedback with technical rigor over performative agreement, requesting reviews via code-reviewer subagent, and verification gates requiring evidence before any status claims. Essential for subagent-driven development, pull requests, and preventing false completion claims.

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Fully autonomous bug hunting pipeline — discover bugs in a scoped area using parallel subagents, independently triage each finding, fix confirmed issues with subagents, then audit all fixes against repo constraints and target platforms. Runs end-to-end without user interaction.

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Catalog-then-fix slop removal on an existing prose draft. Parallel catalog subagents inventory four slop categories (theatrics, overwrought register, corrective antithesis, dramatic short sentences), fix subagents repair only what a catalog names, mechanical lint + frequency analysis bracket the run, and a regression gate (lint delta, word count, cold meaning check) decides whether the result ships. Use when the user says "deslop this draft", "catalog deslop", "strip the AI patterns from this file", or as the final stage of the article-factory and mosaic-writing skills. For writing or redrafting prose from scratch, use the prose skill instead - this skill only repairs an existing draft in place.

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Use this skill when designing, auditing, or troubleshooting behavioral boundaries for Agentforce agents — including topic (now subagent) Scope fields, agent-level system instructions, topic/action filters, the Escalation topic, restricted topics, and Instruction Adherence monitoring. Trigger keywords: agent guardrails, agent out of scope, restrict agent behavior, topic scope, subagent scope, agent fallback, Escalation topic, abuse prevention, action filters. NOT for Trust Layer content filtering (Einstein Trust Layer is a separate product concern), NOT for general topic routing design (use agentforce/agent-topic-design), NOT for prompt template construction (use agentforce/prompt-builder-templates).

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Use when testing, evaluating, or building regression suites for Agentforce agents: conversation testing in Agent Builder, topic (now subagent) coverage and utterance testing, Testing API and AiEvaluationDefinition metadata, Agentforce DX CLI test runs (sf agent generate test-spec, sf agent test create/run/resume/results/list), evaluation metrics (containment rate, escalation rate, CSAT, topic activation accuracy), and post-deploy analytics via Enhanced Event Logs. Triggers: 'how do I test my Agentforce agent', 'agent routes to wrong subagent', 'write utterance tests', 'regression test after topic change', 'measure agent quality', 'agent containment rate', 'run agent tests from the CLI'. NOT for agent creation, topic design, or action contract design — use agentforce/agentforce-agent-creation, agentforce/agent-topic-design, or agentforce/agent-actions respectively.

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Use when designing or reviewing Agentforce topic (renamed subagent in April 2026) structure, including topic boundaries, instruction quality, handoff rules, out-of-scope behavior, and topic-selector strategy. Triggers: 'agentforce subagents (formerly topics)', 'topic design', 'topic selector', 'agent scope boundary', 'handoff conditions'. NOT for restricting what the agent may do or say (topic Scope, action filters, abuse prevention) — use agentforce/agentforce-guardrails. NOT for the mechanics of transferring a live conversation out — Omni-Channel routing and the context package — use agentforce/agentforce-agent-handoff-patterns.

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Delegate implementation work to a dedicated implementer subagent, then review its diff, send it back to iterate, gate on the full test suite, and ship it as a PR. Use this whenever the user wants a separate model to write code, mentions handing off / delegating implementation, asks to work through a plan or spec unit-by-unit with a subagent doing the coding, or wants a review-and-merge loop wrapped around delegated output — and also when resuming such a loop ("keep going", "next unit", "继续下一个"). It encodes constraints that are expensive to rediscover: the implementer self-reports success, must not run the full test suite by default, must not touch git, and its report is a claim rather than evidence. Cursor port of implementation-loop. This loop expects an approved plan or an equivalently precise spec; settle an unsolved high-level goal into a plan first, using the cursor-engineering-mode skill (it ships in this same plugin).

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Coordinates staged or parallel jobs across live-verified coding-agent runtimes (Claude Code, Codex, Cursor, and other installed CLIs) and in-session toolkit subagents. Routes each job by capability and risk tier, isolates parallel writers in git worktrees, captures redacted output, resumes interrupted runs, and blocks completion until an independent arbiter verifies the results. Use when work should be split across multiple runtimes or subagents, run as staged or parallel jobs, and reviewed before handoff. NOT for a single-agent task or the in-session 7-phase flow (use mk:cook / mk:workflow-orchestrator).

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Coordinate complex engineering work across bounded subagents while protecting the main context, preventing edit conflicts, and measuring whether delegation was worthwhile. Use when the user asks to delegate, parallelize, orchestrate, use subagents, fan out a review, or handle a large task with independent workstreams; do not use for small, tightly coupled, or inherently sequential tasks.

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Execute plans via delegate_task subagents (2-stage review).

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Turns a plan phase into a PhaseSpec v1 and dispatches it to a specialist subagent via the Agent tool. Subagent reads files itself, returns a structured result, the result is logged into progress.md. Markdown is the shared state; no in-memory shared store across agents.

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Subagent for GitHub author enterprise enrichment. Runs gh api users/<login> for each unique handle and classifies enterprise vs indie. Invoked by weekly-report or enterprise skills; runs as Explore subagent so the orchestrator's context stays small.

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