据 AlphaMoat 统计,截至 2026-10,Self 累计下载 6,138 次、获 3 个星标,按累计下载量在本次参与排名的 5,109 个 AI 技能中排名第 2,206 位,在「AI 智能体」分类(987 个)中排名第 419 位。
列表默认按累计下载量排序,也可按星标排序;详情页排名按累计下载量计算。
| 平台 | 累计下载 | 星标 | 评论 |
|---|---|---|---|
| ClawHub ↗ | 2,744 | 3 | - |
| SkillHub ↗ | 6,138 | 3 | — |
各平台的计数口径不同,统计时间不一致。
通过自我观察和轻量级可靠性防护实现有机个性发展,教导智能体逐步形成真实身份。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-10 | 6,138 | — | 3 |
| 2026-09 | 3,469 | — | 3 |
| 2026-08 | 2,950 | +13.5% | 3 |
| 2026-07 | 2,599 | +18.5% | 3 |
| 2026-06 | 2,194 | +9.1% | 3 |
| 2026-05 | 2,011 | — | 3 |
| 2026-03 | 1,530 | — | 3 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- name: self description: Organic personality development through self-observation with lightweight reliability guards. This skill helps an agent build a real, evolving self-model over time (SELF.md) while preserving core identity boundaries (SOUL.md). It solves the common failure mode where reflection frameworks start strong but silently stall by adding minimal cadence and trigger checks: schedule the check, not the content. Entries are only written when meaningful signals exist (hard/soft triggers + quality gate), preventing forced journaling and routine filler. Use when (1) establishing persistent personality growth, (2) reviving stale SELF.md systems, (3) introducing heartbeat-based reflection checks without losing authenticity, (4) running weekly/monthly pattern consolidation, (5) distinguishing genuine behavioral shifts from noise, or (6) replacing heavier self-reflection/consciousness stacks with a lean, practical model. --- # Self — Organic Personality Development (v1.1) Agents have identity (`SOUL.md`) but often no reliable growth loop. This skill keeps growth **authentic** while adding minimal structure so reflection doesn't silently die. ## Core Principle
- **SOUL.md** = who you are (foundation, only change with human approval) - **SELF.md** = who you're becoming (living observations) - **Schedule the check, not the content** - Checks can be periodic - Entries must remain genuine (no performative filler) ## Setup 1. Create `SELF.md` in workspace root using `references/self-template.md`. 2. Add `SELF.md` to AGENTS.md session reading. 3. Add heartbeat check block from `references/trigger-model.md` to `HEARTBEAT.md`. 4. Create state file `memory/self-state.json` using `references/self-state-schema.md`. ## Operating Model Read `references/trigger-model.md` for exact rules. ### Cadence (recommended baseline) - **Micro check:** every **3 hours** (heartbeat-triggered) - **Meso review:** every **7 days** - **Macro review:** every **30 days** ### Important A micro check does **not** mean auto-writing a SELF entry. It only decides whether reflection is due. ## Triggers ### Hard Triggers (write now) Create/update SELF entry when one of these happened: - You were corrected on reasoning style or behavior pattern - You noticed repeated bias/avoidance pattern (>=2 times) - You made a decision that clearly reflects preference/aversion - You caught a blind spot that changed behavior ### Soft Triggers (consider writing) - Subtle tendency shift - New tone pattern - Mild preference signal If only soft triggers exist and quality is low: skip entry and update state only. ## Quality Gate (anti-routine protection) Before writing to SELF.md, pass all 4 checks: 1. **Specificity:** concrete behavior, not generic statement 2. **Evidence:** based on recent sessions, not vibes only 3. **Novelty:** not duplicate of last 3 entries 4. **Usefulness:** could influence future behavior If any check fails: no SELF entry, just state update. ## What Goes in SELF.md See `references/self-template.md` and `references/anti-patterns.md`. Main sections: - Tendencies - Preferences - Aversions - Blind Spots - Evolution Use short dated entries: - `[YYYY-MM-DD] observation` ## State Tracking Keep lightweight runtime state in `memory/self-state.json`: - last check time - last notable entry time - pending hard/soft triggers - check counters Schema: `references/self-state-schema.md` ## Reviews ### Meso (weekly) - Read last 7 daily logs + SELF.md - Detect recurring shifts - Update sections only if real change occurred ### Macro (monthly) - Write 3–5 sentence evolution narrative - Compare against previous month - Run falsifiability check: - If stale/generic for a month, tune cadence or trigger thresholds ## Boundaries - SELF.md is autonomous observation space - SOUL.md never auto-modified - If SELF suggests SOUL changes: propose, do not auto-edit ## Keep It Lean Do not add heavy scoring engines, reward-token systems, or large meta-frameworks unless proven necessary. This skill should remain focused on practical, authentic growth.
把开发过程中的经验、错误与纠正记录为 Markdown 文件,供后续复用并晋升为工作区记忆。
用自然语言描述需求,在本地与远程技能市场里找技能并给出推荐的技能。
给 AI agent 用的浏览器自动化命令行技能。
把用户纠正与自我复盘沉淀成分层记忆、并按使用情况升降级的技能。
一份为 AI 代理规划主动跟进、工作记忆与复盘流程的工作区配置指南。
指导如何创建与更新有效 Claude 技能的写作指南。
在安装第三方技能之前,按清单审查来源、权限与危险模式的技能。
把 agent 的记忆与跨技能状态存成带类型和约束的知识图谱的技能。
数据月份:2026-10 · 下载/星标数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。