Claude Skill

memory-management

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

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Download thinkinaixyz-deepchat-resources_skills_memory-management-f886d6e.zip · 1 KB
Part of thinkinaixyz/deepchat — 22 skills

Install

skills CLI npx skills add https://github.com/ThinkInAIXYZ/deepchat/tree/dev/resources/skills/memory-management
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install thinkinaixyz-deepchat@llmmart
Git git clone https://github.com/ThinkInAIXYZ/deepchat.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole thinkinaixyz/deepchat collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

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.

Files (deepchat)
  • SKILL.md 3.3 KB
    ---
    name: memory-management
    description: Guide the agent to recall, remember, and route durable learning into Memory, Skills, Scheduled Tasks, or Tape.
    ---
    
    # 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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