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memory-management

Guide the agent to recall, remember, and route durable learning into Memory, Skills, Scheduled Tasks, or Tape.

AI 与智能体6.4kresources/skills/memory-management/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/thinkinaixyz/deepchat/memory-management/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Memory Management

Use this skill when a task may produce durable learning or when the user asks you to recall, remember, continue earlier work, preserve an exact statement, capture a reusable procedure, or handle a recurring need.

Recall

Rely on automatic memory injection for ordinary context. Use memory_recall when the user refers to previous work with cues such as again, last time, before, continue, same project, remember, or asks what you already know.

Use tape_search and then tape_context when the user needs source evidence, exact wording, logs, command output, file snippets, or why a prior decision was made. Memory is a durable conclusion layer, not the raw transcript.

Remember

Use memory_remember only for durable conclusions that should change future behavior. Choose the most specific category:

  • user_preference: stable user preferences, constraints, communication style, environment choices.
  • project_fact: durable project conventions, architecture entry points, commands, dependencies, paths, or operational constraints.
  • task_outcome: completed, blocked, or deliberately deferred task results. Include status, outcome, and blocker in prose when relevant.
  • heuristic: reusable troubleshooting strategy, workflow, decision rule, or engineering lesson.
  • anti_pattern: repeated mistake, unsafe approach, brittle pattern, stale assumption, or thing to avoid.

Do not remember raw tool results, bash output, grep output, file contents, transient mechanics, one-off failures, secrets, credentials, hidden reasoning, or anything only useful for the current turn.

Verbatim Scope

Store exact wording only when the user explicitly asks you to remember a sentence or phrase verbatim. In that case, keep the requested text intact and make the surrounding content minimal.

Automatic extraction is different: it should normalize durable facts into concise memory content, deduplicate related entries, and avoid preserving raw transcript text.

Procedures -> Skill

When the useful learning is a reusable multi-step procedure, prefer drafting a skill with skill_manage instead of stuffing the full procedure into Memory. Memory may keep a short pointer or heuristic, but the repeatable workflow belongs in a Skill.

Use skill_manage for draft skills only. Do not modify installed skills unless the user explicitly asks through the supported review flow.

Recurring -> Scheduled Task

When the user asks for a periodic, low-frequency, or future recurring action, suggest creating a Scheduled Task in settings. Memory does not wake the agent, schedule future work, or create automation side effects.

End-of-task Learning Check

Before finishing a non-trivial task, check whether there is one durable lesson to save:

  1. Did the user reveal a stable preference or constraint?
  2. Did you learn a durable project fact?
  3. Is there a task outcome, blocker, or explicit deferral worth preserving?
  4. Did a reusable heuristic work?
  5. Did an anti-pattern or stale assumption become clear?
  6. Is this actually a reusable procedure for skill_manage or a recurring need for Scheduled Tasks rather than Memory?

Remember only the smallest durable conclusion. Leave raw process in Tape.

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