원클릭으로 Manus에서 모든 스킬 실행

session-start

스타4

포크0

업데이트2026년 7월 3일 17:41

Check memory for in-progress tasks and active TODOs at the start of each session. Use at the beginning of every new conversation.

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

Manus에서 실행

출처

alexfayers

alexfayers/llm-prompts

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Manus에서 실행

session-start

At the start of every session, before responding to the user's first message, check memory for in-progress work using compact mode to minimise token usage:

read_graph(project="<repo-name>") to surface recent entities for the current workspace.
CRITICAL - do NOT skip this step or substitute read_graph results. Run both of these calls with compact=true:
- search_all_projects(query="task", status="in-progress", compact=true)
- search_all_projects(query="task", status="planned", compact=true) These are the only authoritative source for the task summary. read_graph only returns 10 recent entities from one project and will miss tasks in other scopes. compact=true omits observations to save tokens - you only need entity names and statuses for the summary.
Present the task summary grouped by project. Show in-progress tasks first, then planned. Include ALL results - do not truncate or summarise away tasks.
If nothing is in progress or planned anywhere, proceed normally without mentioning the check.
Run llm-prompts update --check to see if any tool sources have upstream updates available. If updates are found, mention them to the user.
Call the memory tools (read_graph, search_all_projects, search_nodes, etc.) directly - they are ordinary tools in your catalog. Do NOT run any tool-discovery step to "find" or "check availability of" memory first (e.g. list_mcp_resources, listing servers): that lists resources, not tools, and an empty result does not mean memory is unavailable. If and only if your harness hides tool schemas behind an explicit ToolSearch/deferred-tools step (Claude Code), pre-load them once with select:mcp__memory__add_observations,mcp__memory__read_graph,mcp__memory__search_nodes,mcp__memory__create_entities; otherwise there is nothing to pre-load - just call the tools.

이 저장소의 다른 Skills

같은 저장소

git-usage

alexfayers/llm-prompts

Rules and style preferences for the usage of git. Use before you interact with git in any way.

2026-07-164

handoff

alexfayers/llm-prompts

Write a handoff document so a fresh session (or another agent) can resume multi-session work with full context. Use when the current session is ending mid-effort, context is running high, or the user asks to "hand off", "hand over", or prepare the next session/slice.

2026-07-124

session-end

alexfayers/llm-prompts

Checklist for wrapping up a session - persist memory, check TODOs, and ensure nothing is lost. Use before marking a task complete or ending a conversation.

2026-07-124

refine-plan

alexfayers/llm-prompts

Evaluate and refine a plan before implementation begins. Use once you think you are ready to present a plan or design to the user.

2026-06-164

retrospective

alexfayers/llm-prompts

Analyse recent session transcripts to extract learnings, discover pain points, and persist them into memory/skills/rules. Run manually when the retrospective counter is due (session-end reminds you at 5+).

2026-06-154

tidy-code

alexfayers/llm-prompts

Reduce the amount of code in a changeset or file - remove duplication, dead code, redundancy, and over-verbose constructs - while preserving behaviour. Use when asked to tidy, shrink, deduplicate, DRY up, or simplify code.

2026-06-124

name	session-start
description	Check memory for in-progress tasks and active TODOs at the start of each session. Use at the beginning of every new conversation.

session-start

At the start of every session, before responding to the user's first message, check memory for in-progress work using compact mode to minimise token usage:

read_graph(project="<repo-name>") to surface recent entities for the current workspace.
CRITICAL - do NOT skip this step or substitute read_graph results. Run both of these calls with compact=true:
- search_all_projects(query="task", status="in-progress", compact=true)
- search_all_projects(query="task", status="planned", compact=true) These are the only authoritative source for the task summary. read_graph only returns 10 recent entities from one project and will miss tasks in other scopes. compact=true omits observations to save tokens - you only need entity names and statuses for the summary.
Present the task summary grouped by project. Show in-progress tasks first, then planned. Include ALL results - do not truncate or summarise away tasks.
If nothing is in progress or planned anywhere, proceed normally without mentioning the check.
Run llm-prompts update --check to see if any tool sources have upstream updates available. If updates are found, mention them to the user.
Call the memory tools (read_graph, search_all_projects, search_nodes, etc.) directly - they are ordinary tools in your catalog. Do NOT run any tool-discovery step to "find" or "check availability of" memory first (e.g. list_mcp_resources, listing servers): that lists resources, not tools, and an empty result does not mean memory is unavailable. If and only if your harness hides tool schemas behind an explicit ToolSearch/deferred-tools step (Claude Code), pre-load them once with select:mcp__memory__add_observations,mcp__memory__read_graph,mcp__memory__search_nodes,mcp__memory__create_entities; otherwise there is nothing to pre-load - just call the tools.