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agent-toolkit
agent-toolkit에는 eai-org에서 수집한 skills 18개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.
이 저장소의 skills
Audit the current project's agent-memory and, block by block, relocate each entry into a user-controlled home (project doc/skill/rule or user-level skill/rule) or archive it — draining memory so nothing uncontrolled accumulates in the agent's context.
How to write texts meant to be published by humans for other humans.
Fresh-eyes review of a changeset by a fresh-context agent — catches regressions and correctness issues the authoring context reads past.
Check how much of a ticket is already implemented — split it into requirement blocks, judge each against the code, and save a human-readable TICKET-STATUS report in the planning dir.
Author or refine a skill for maximum token economy without losing intent. Use when creating any new skill or editing an existing `SKILL.md`.
Audit what auto-loads into an agent session's context window and suggest lean, reversible fixes to cut startup tokens.
Assist a human reviewing a pull request or branch locally — diff a source branch against its target (auto-detected or from a PR link) and return concise, human-voice review comments with file and line locations. Read-only, never posts.
Triage a ticket or ticket set before work starts — compare it against the codebase and save a review covering verdict, feature walkthrough, and only the high-cost questions worth raising.
Verify the engineer is ready to implement a feature — a teach-back conversation over a .TICKET-REVIEW.md where they explain the feature in their own words and the agent probes and corrects.
Turn a refined requirements document into a structured implementation PLAN.md a fresh session can execute. Planning only — decides the "how", not the "what". Invoke manually only.
Turn a ticket or requirements document into a concise QA manual-test file a non-author can follow. Invoke manually only.
Fetch all reviewer comments from a pull request URL (GitHub, Azure DevOps, …) and save them as a self-contained markdown PR-REVIEW file in the task's planning directory. Fetch only — no fixing or replying.
Fetch one or more tickets/issues from their tracker (Azure DevOps, Jira, GitHub, …) and save each as a self-contained markdown ticket file. Fetch only — no analysis or planning.
Refine a development ticket — or brainstorm a raw idea — into a validated, self-contained REQUIREMENTS document — the "what", verified against the codebase. Invoke manually only.
Rewrite or refine a doc for maximum token economy without losing any rule or intent. Use for docs kept in version control and regularly re-read by agents; skip throwaway docs like plans.
Triage a fetched PR review with the user, comment by comment — address, partial, or push back — drafting each reply and producing a REQUIREMENTS file for the accepted code changes. Takes the PR-REVIEW file produced by fetch-pr-review. Invoke manually only.
Run nx format, lint, test, and build on affected or specified projects, then fix unambiguous failures
Capture durable user feedback into the governing skill/doc, or propose creating a new skill when no suitable one exists, so future sessions don't repeat the mistake. Use when the user rejects, reverts, or overrides the agent's output or approach on something a skill/doc covers or should cover, and when manually invoked to improve or create guidance.