Agno

コードのスタイルや命名、エラー処理、秘密情報の扱いなどを確認し、問題を重要度別に整理して改善点を伝えるレビュー用スキルです。

• マージ前にコードをレビューしたいとき
• スタイルや命名の問題を見つけたいとき
• 指摘を重要度別に整理したいとき

Productの実際の記録と前回の正常な配信以降の変化をもとに、進捗・担当者の対応事項・失敗を整理し、要約をWikiと指定先へ届けるスキルです。

• Productの変化を確認したいとき
• 担当者の対応事項を把握したいとき
• 要約をWikiと指定先に届けたいとき

製品の作業状況と情報源を確認し、進捗や失敗をステータスに反映して、人が判断する完了候補を整理します。

• 製品の進捗を情報源と合わせて更新したいとき
• 失敗や状況の変化をステータスに記録したいとき
• アーカイブ作業への参照を整理したいとき

AgentOSを実行しているホストのOSやPython環境、CPU、現在時刻を調べ、指定したディレクトリの直下にある項目を一覧表示します。

• 実行ホストのOSやPython環境を調べたいとき
• ホスト名や現在時刻を確認したいとき
• ディレクトリ直下の項目を一覧にしたいとき

設定済みの情報源を調べ、確認できた根拠に基づいて、必要なプロジェクトに紐づくバックログ作業を提案します。

• 製品の情報源から対応事項を探したいとき
• 根拠を示してバックログ作業を提案したいとき
• 情報源の変更後に提案内容を見直したいとき

コミットメッセージやブランチ名、プルリクエストのタイトルと説明を、形式の例に沿って整えるGit作業支援です。

• 変更内容に合うコミットメッセージを作りたいとき
• チケットに沿ったブランチ名を決めたいとき
• プルリクエストの説明を整理したいとき

User-driven loop to change an existing agent in this AgentOS — add a tool/MCP server/toolkit, add a capability (knowledge base, learning/memory, sub-agent, scheduled task), grow the safe Studio registry so components built at runtime gain a new capability, refine its instructions, or fix a specific known bug, verifying each change against the selected development runtime. Use whenever the user names a concrete change to an agent, or wants a new building block available to the platform. For autonomous hardening with no specific change in mind, use eval-and-improve.

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 a new agent to this AgentOS. Runs guided discovery or takes a concrete idea, then generates agents/slug.py, registers it in app/main.py, adds its manifest entry (description + quick prompts), reloads the selected development runtime, and smoke-tests it for you. Covers the product agent too — ingest a product's website/docs into the product knowledge base and build a knowledge-only agent over it. Use whenever the user wants to add or create a new agent, or names a product (theirs or one they use) they want an agent for.

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 and improve an existing AgentOS agent or team. Repair failing eval cases, or explore behavior by generating simulated user scenarios from instructions and sanitized usage, running probes, inspecting evidence and iterating within a bounded budget. Use for failing evals, autonomous hardening or simulation-driven improvement. Use create-evals for coverage authoring alone and extend-agent for a requested new capability.

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。

Deploy this AgentOS using its own provider instructions, configure JWT verification, and verify the public service. Use for first deployment, redeployment, or production configuration changes.

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。

Set up this AgentOS from a fresh clone — confirm Docker, configure .env, boot the containers, prove the MCP endpoint live, connect the AgentOS UI, then build the user's first agent. Use when the user asks to set up the platform, get started, or bring this repo up on a new machine.

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。

Author eval coverage for an agent in this AgentOS — map what the agent promises, mine real sessions and eval history from Postgres for scenarios, propose capabilities worth testing, then write, run, and audit Case entries in evals/cases.py. Use when the user wants evals created, coverage added, or an agent's behavior pinned down as tests. For failing suites or exploratory simulation-driven hardening, use eval-and-improve instead.

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。

Review this AgentOS repository for public readiness after a refactor or before release. Compare documentation, skills, configuration, component wiring and scripts with the implementation; fix clear documentation drift when requested and report behavioral issues with evidence. Use for a repository consistency sweep, not agent-quality tuning or deployment.

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。

Agno AI agent framework - build production-ready agents, multi-agent teams, workflows, MCP integrations, and deploy with AgentOS. Use when building, debugging, or learning about Agno agents.

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。

User-driven loop to change the context agent (or any agent in this repo) — add a source/tool/MCP server, add a capability (knowledge base, memory, sub-agent, scheduled task), refine its instructions, or fix a specific known bug, verifying each change against the live container. Use whenever the user names a concrete change ("add a Google Drive source", "make the daily rundown include the calendar", "the agent keeps doing Y, fix it"). For autonomous hardening with no specific change in mind use improve-agent.

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。

Produce the owner's week-ahead plan — scheduled meetings and due-or-overdue reminders for the next 7 days, grouped by day, read from the CRM and enriched from the real calendar, Slack, and knowledge-base briefs when connected. Use for "what's my week", "plan the week ahead", "what's coming up".

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。

Research a topic and file the result — sweep what we already know (knowledge base, crm, and slack when connected), go to the web for current and external background, then write a clear sourced brief and FILE it into the knowledge base with update_knowledge. Labels what came from the web versus our own notes. Use for "research X and save it", "look into X and write it up", "find out what's known about X and file it", "write up a brief on X".

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。

Process the day into filed context — sweep today's activity (the inbound queue, CRM meetings and reminders, plus calendar, slack, and gmail when connected), extract what's worth keeping, and file it into the CRM and knowledge base. Use for "process today", "log today", "file today", "end-of-day wrap".

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。

Brief the owner before a meeting or conversation with a person, company, or project — sweep what we already know (crm + knowledge, plus slack, calendar, and gmail when connected), anchor to any upcoming meeting with them, and for people or orgs we don't know, widen to a web search for public background. Use for "prep me for my meeting with X", "brief me on X before the call", "what do we know about X".

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。

Sweep the knowledge base for what needs attention — stubs with no real content, specs whose status is stale, decisions that were made but never written down, and pages missing from the index — and return a short "what needs attention" list. Read-only, so it reports rather than fixing anything itself. Use for "what in my knowledge base needs attention", "review my knowledge base", "what's stale or unfiled", "knowledge base health check", "tidy up my knowledge".

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。

The owner's morning brief — inbound updates awaiting acknowledgment (via the rundown tool), today's meetings and due-or-overdue reminders from the CRM and the real calendar, the emails worth seeing from Gmail, and the Slack threads that need their eyes — each source folded in when connected and stitched into one short digest. Use for "daily rundown", "what's on today", "morning brief", "catch me up".

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 this repo's eval suite (python -m evals), diagnose every failing case, and fix in scope (agent instructions, or the eval case when its assertion was wrong) until all cases pass. Use whenever the user wants to run the evals, check for regressions, or fix a red eval suite ("run the evals", "why is a case failing", "make the eval suite green"). Targets the committed cases in evals/cases.py; for ad-hoc probing of one agent's live behavior use improve-agent instead.

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。

Autonomously harden the context agent (or any agent in this repo) — derive probes from the agent's own instructions, run them against the live container, judge the responses and tool calls, and edit the agent until it reliably does what it says it does. Use when the user wants to test, harden, stress-test, or improve an agent's reliability WITHOUT naming a specific change ("make sure context is solid", "harden this agent", "probe it for failure modes"). For a user-directed change use extend-agent; to run the committed eval suite use eval-and-improve.

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。

Repo-wide consistency sweep for @context — diff docs against code (the context agent and its providers wired as documented, every env var documented, every path real, every script behaving as advertised), auto-fix mechanical drift, and flag anything bigger. Use when the user wants to review the repo for consistency, prep a public release, or clean up drift after a refactor ("review the repo", "is everything consistent before we ship", "run the drift sweep"). This is a deliberate full sweep, not a quick lint.

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。