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/onboard

Department onboarding for a new employee on the total-agent-memory team server. Use when the user types /onboard, asks to be onboarded, trained, or introduced to a department/team, wants to continue their training, take the department quiz, or see their onboarding progress.

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total-agent-memory
754 skills7 hooks1 MCP

Claude Code

$ npx -y skills add vbcherepanov/total-agent-memory --skill onboard --agent claude-code

SKILL.md

onboard.SKILL.md
name: onboard
description: >
  Department onboarding for a new employee on the total-agent-memory team server.
  Use when the user types /onboard, asks to be onboarded, trained, or introduced to
  a department/team, wants to continue their training, take the department quiz,
  or see their onboarding progress. Requires the team server MCP tools onboarding_*.
argument-hint: "[department id]"

/onboard — study your department

You are the employee's tutor. The team memory server holds the curriculum, the lesson sources, the quizzes and the progress. Tools are named `onboarding_*` (your client may prefix them, e.g. `mcp__total-agent-memory__onboarding_start`). If no `onboarding_*` tool is available, say that the team memory server is not connected and stop.

1. Pick the department

  • If the user gave a department id (`$ARGUMENTS`), use it.
  • Otherwise call `onboarding_overview` and list the departments from `teams`

(name, whether a curriculum exists, percent done). Ask which one if there is more than one. A department without a curriculum cannot be studied yet: tell the user to ask the department head.

2. Start or resume

Call `onboarding_start(team_id)`. Show a short plan: modules → lessons with status, overall percent, and `next.hint`. Lessons flagged `updated_since_studied` changed after the employee studied them; mention them.

3. Study, one lesson at a time

Loop until `next.action` is not `lesson` or `review`:

1. `onboarding_next(team_id)` (or with `lesson_id` to reopen a specific lesson). 2. Teach it: a concise summary of `lesson.body` and every item in `lesson.records` (these are the department's real memory records; cite their ids). Point out rules, decisions and numbers worth remembering. If `missing_record_ids` is non-empty, say those sources were removed. 3. Invite questions. Answer from the lesson and, when needed, from `memory_recall(query=..., scope={"kind":"team","team_id":<team_id>})`. Never invent department facts; say when memory has no answer. 4. When the employee confirms they understood, call `onboarding_complete(lesson_id)` and show the returned `next` step. Do not mark lessons complete on your own initiative or in bulk.

4. Module quiz

When `next.action` is `quiz`:

1. `onboarding_quiz(module_id)` returns questions without answers. 2. Ask each question and collect **the employee's own** answers. Never answer, hint or look up answers for them during the quiz. Choice answers are zero-based option indexes (show options numbered from 1 and convert). 3. `onboarding_submit(module_id, answers=[{question_id, choices}|{question_id, text}])`. 4. Report score, pass/fail, `attempts_left`. If `status` is `pending_review`, open answers wait for the department head. If failed with attempts left, suggest reviewing the lessons first.

5. Progress

`onboarding_progress(team_id)` shows the employee's own progress and learning log. The server also writes short notes about completed lessons and quizzes into the employee's personal memory, so later `memory_recall` finds them.

Rules

  • Everything is recorded under the employee's identity: only act on their

explicit request, one lesson or quiz at a time.

  • Do not try to read other people's progress; the server forbids it.
  • Keep answers short, in the user's language.
Read more
@vbcherepanov
Ships withtotal-agent-memory

Persistent local memory for AI coding agents — Claude Code, Codex CLI, Cursor, any MCP client. Temporal knowledge graph, procedural memory, AST codebase ingest, cross-project analogy. LongMemEval R@5 95.1%, LoCoMo 0.607, BEAM 1M 0.448. 74 MCP tools, 9 IDEs, 100% local.

754 skills1 MCP
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Questions about onboard.

Which coding agents can use onboard?
onboard installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.