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knowledge-agent

Build focused knowledge bases from claude-mem observations, filtered by topic, project, date, or file. Load selected records into an AI conversation to ask contextual follow-up questions about past decisions, fixes, and work patterns.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Build and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused "brains" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.

thedotmack/claude-mem
설치 방법 보기

이럴 때 유용합니다

  • Compiling knowledge about a specific technical topic
  • Reviewing decisions made during a chosen period
  • Asking follow-up questions about a service's past bug fixes
  • Refreshing a knowledge base with newly recorded work

포함된 파일(1)

  • SKILL.md2.4 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Knowledge Agent

Build and query AI-powered knowledge bases from claude-mem observations.

What Are Knowledge Agents?

Knowledge agents are filtered corpora of observations compiled into a conversational AI session. Build a corpus from your observation history, prime it (loads the knowledge into an AI session), then ask it questions conversationally.

Think of them as custom "brains": "everything about hooks", "all decisions from the last month", "all bugfixes for the worker service".

Workflow

Step 1: Build a corpus

build_corpus name="hooks-expertise" description="Everything about the hooks lifecycle" project="claude-mem" concepts="hooks" limit=500

Filter options:

  • project — filter by project name
  • types — comma-separated: decision, bugfix, feature, refactor, discovery, change
  • concepts — comma-separated concept tags
  • files — comma-separated file paths (prefix match)
  • query — semantic search query
  • dateStart / dateEnd — ISO date range
  • limit — max observations (default 500)

Step 2: Prime the corpus

prime_corpus name="hooks-expertise"

This creates an AI session loaded with all the corpus knowledge. Takes a moment for large corpora.

Step 3: Query

query_corpus name="hooks-expertise" question="What are the 5 lifecycle hooks and when does each fire?"

The knowledge agent answers from its corpus. Follow-up questions maintain context.

Step 4: List corpora

list_corpora

Shows all corpora with stats and priming status.

Tips

  • Focused corpora work best — "hooks architecture" beats "everything ever"
  • Prime once, query many times — the session persists across queries
  • Reprime for fresh context — if the conversation drifts, reprime to reset
  • Rebuild to update — when new observations are added, rebuild then reprime

Maintenance

Rebuild a corpus (refresh with new observations)

rebuild_corpus name="hooks-expertise"

After rebuilding, reprime to load the updated knowledge:

Reprime (fresh session)

reprime_corpus name="hooks-expertise"

Clears prior Q&A context and reloads the corpus into a new session.

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같은 저장소의 스킬

Agent Cost Report

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Turn agent activity and transcript token counts into a cost report organized around completed outcomes. Separate estimates from measured spending, examine waste and rework, and export readable HTML with supporting JSON, CSV, and evidence.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Reviewing weekly agent spending and completed work
  • Comparing costs per completed outcome
  • Investigating the cost of loops and rework
thedotmack/claude-mem10.2만2026년 10월 19일 업데이트

babysit

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Monitor a pull request through reviews and automated checks, verify reported issues against the code, and make focused fixes. Repeat testing and review checks until actionable comments and unresolved threads are cleared and the request is ready to merge.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Monitoring a pull request while automated checks run
  • Verifying and fixing review comments
  • Checking unresolved threads before a merge
thedotmack/claude-mem10.2만2026년 10월 19일 업데이트

build-and-release

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Delegate a coding task to a subagent that runs build, merges the ready pull request, and continues from the updated main branch into release, connecting implementation and release work in one automated sequence.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Delegating a coding task through release
  • Connecting a ready PR merge to release work
  • Running build and release in sequence
thedotmack/claude-mem10.2만2026년 10월 19일 업데이트

ccs-align

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Check a local claude-mem worker, refresh viewer-specific caches of important observations, and exclude or restore records without deleting history. Inspect rules across shared, project, and agent layers, then append conflicts to a report.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Checking worker health and refreshing important observations
  • Excluding cached records while preserving source history
  • Restoring previously excluded observations to a cache
thedotmack/claude-mem10.2만2026년 10월 19일 업데이트

childhood

무료

Monitor a shipped release by checking published packages, live services, installed plugins, and late CI results or user reports. Verify regressions, prepare authorized fixes, and report release health with evidence and any remaining verification gaps.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Checking package contents after publication
  • Verifying changed user flows in production
  • Confirming installed plugins use the shipped version
thedotmack/claude-mem10.2만2026년 10월 19일 업데이트

claude-mem-install

무료

Set up claude-mem in Cursor with a local or remote worker, the process that runs its work. Follow configuration steps for remote inference through cmem.ai or a local observer using the host's login.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Installing claude-mem with a local worker in Cursor
  • Connecting Cursor to a remote claude-mem worker
  • Configuring host-login or cmem.ai inference
thedotmack/claude-mem10.2만2026년 10월 19일 업데이트

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