According to AlphaMoat, as of 2026-10, Self has 6,138 downloads and 3 stars — ranked by downloads #2,206 among 5,109 AI skills in this ranking, and #419 of 987 in AI Agent.
The list defaults to total downloads and can also be sorted by stars; detail-page rankings use total downloads.
| Platform | Downloads | Stars | Comments |
|---|---|---|---|
| ClawHub ↗ | 2.7K | 3 | - |
| SkillHub ↗ | 6.1K | 3 | — |
Platforms count differently and update at different times.
Organic personality development through self-observation with lightweight reliability guards. Teaches agents to grow authentic identity over time by combinin...
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-10 | 6.1K | — | 3 |
| 2026-09 | 3.5K | — | 3 |
| 2026-08 | 3.0K | +13.5% | 3 |
| 2026-07 | 2.6K | +18.5% | 3 |
| 2026-06 | 2.2K | +9.1% | 3 |
| 2026-05 | 2.0K | — | 3 |
| 2026-03 | 1.5K | — | 3 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 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.
Records learnings, errors and corrections as Markdown files for later reuse and promotion into workspace memory.
Finds skills in local and remote catalogs from a plain-language request and recommends what to install.
A browser-automation command line skill for AI agents.
Turns corrections and self-review into tiered memory and promotes or archives it by use.
A workspace setup guide for planning proactive follow-up, working memory and review routines for an AI agent.
A guide to creating and updating effective Claude skills.
Reviews a third-party skill's source, permissions, and danger patterns against a checklist before it is installed.
Stores agent memory and cross-skill state as a typed, constraint-checked knowledge graph.
Data as of 2026-10. Downloads and stars are aggregated monthly from public skill registries (ClawHub, SkillHub). See data methodology.