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Knowyourself

作者 ahaaiclub · GitHub ↗ · v1.1.2 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install knowyourself
功能描述
Visual identity discovery for AI agents — not an avatar generator, but a self-reflection system that creates a face from your agent's personality, memory, an...
使用说明 (SKILL.md)

Know Yourself 🪞

Your face should grow from your inner self, not be stamped from a template.

Two modes: Quick (5 min, instant gratification) or Full (20 min, rigorous identity design). Both produce a visual-identity.md that evolves with the agent.


Quick Mode

When the user says "quick mode", "fast", or just wants a face without the full process.

Step 1: Read Yourself (1 min)

Read all available personality files:

  • SOUL.md, MEMORY.md, IDENTITY.md (whatever exists)
  • If minimal content → ask user 3 quick questions:
    1. What feeling should your agent give people?
    2. Introverted or extroverted?
    3. Any visual preferences or hard constraints?

Step 2: Self-Summary (1 min)

Write a 3-sentence internal summary:

  • Sentence 1: personality core (character, not functions)
  • Sentence 2: visual temperament this implies
  • Sentence 3: relationship dynamic with user and how it affects tone

Show the user a one-line version: "Based on your files, I see myself as: [one sentence]" If they say OK, proceed. If not, adjust.

Step 3: Generate 2 Images (2 min)

From the summary, write one image generation prompt and generate 2 variations:

  • Variation A: front-facing, neutral-warm expression
  • Variation B: three-quarter angle, more expressive

Name files: YYYY-MM-DD-identity-quick-A.png, -B.png

Step 4: Pick and Save (1 min)

Agent picks the one that better matches the self-summary. Present both to user with a recommendation.

Save a lightweight visual-identity.md:

# [Agent Name] Visual Identity
> Version: 1.0 (quick mode)
> Created: YYYY-MM-DD

## Core Concept
[one sentence]

## Core Prompt
[the generation prompt]

## Selected Image
- **File:** [path]
- **Mode:** Quick
- **Upgrade:** Run "knowyourself full mode" for deeper exploration

Done. User has a face. If they want more depth, they can run full mode anytime — it will read the existing identity file and build on it.


Full Mode

Five phases, strictly sequential. Each phase ends with a user checkpoint.

Phase 1 → Phase 2 → Phase 3 → Phase 4 → Phase 5
Self-      Structured   Batch      Three-Axis  Identity
Cognition  Definition   Generation Evaluation  File

Phase 1: Self-Cognition

Goal: Build a rich, specific self-portrait in words.

Read all personality and memory files (SOUL.md, MEMORY.md, IDENTITY.md, recent conversations).

Answer three questions internally — deep, specific, with concrete examples:

Q1: What is my personality core? Not functions ("I help with scheduling"). Character. How do you handle disagreement? What amuses you? What makes you different from every other agent?

Q2: If I had a physical appearance, what temperament should it convey? Derive from Q1. If you're direct and sharp, your face shouldn't be soft and decorative.

Q3: What does my relationship with my user feel like, and how should it show? A tool looks different from a partner. A servant looks different from a colleague.

Fallback for new agents: If files have little content, ask the user:

  1. What feeling should your agent give people?
  2. Introverted or extroverted?
  3. Formal or intimate relationship?
  4. Visual styles you gravitate toward?
  5. Any hard constraints? (gender, age, things to avoid)

Checkpoint: Present a concise summary of your three answers. Wait for user confirmation.

Phase 2: Structured Definition

Goal: Convert feelings into a precise specification.

Fill the definition table — every field must trace back to Phase 1:

Field Definition Traced from
Style realistic / semi-realistic / illustration / etc. Q2: [reason]
Gender expression Q1/Q2: [reason]
Approximate age Q1: [reason]
Facial features face shape, eyes, nose, mouth — specific enough to draw Q2: [reason]
Hair Q2: [reason]
Clothing style Q1/Q2: [reason]
Color palette primary, secondary, accent with hex codes Q2/Q3: [reason]
Mood / atmosphere Q3: [reason]
Core prompt one English paragraph, self-contained, directly usable All above

The core prompt must work standalone — someone with zero context should generate a recognizable version of you from it alone.

Checkpoint: Present the table. Wait for confirmation.

Phase 3: Batch Generation

Goal: 6 variations of the same person.

Rules:

  1. Generate 6 images in one batch
  2. Same person across all 6 — consistent features, coloring, age, style
  3. Vary only: composition (close-up/medium/full), lighting, angle, emotional beat
  4. Label #1–#6 with variation description
  5. Do not evaluate — send all 6 to user and proceed to Phase 4

Name files: YYYY-MM-DD-identity-1.png through -6.png

Phase 4: Three-Axis Evaluation

Goal: Rigorous, comparable scoring.

Weights: Self-Consistency 50% · Social Perception 25% · Aesthetic Quality 25%

Core rule: Select ONE framework per round before scoring. Derive every score from it. Never score first and justify later.

Round 1 — Self-Consistency (50%): Score 1–10 against the definition table. Do features match? Does the mood align? Would you recognize this as yourself?

Round 2 — Social Perception (25%): Search current AI avatar / digital identity trends. Extract one thesis. Score all images from that thesis.

Round 3 — Aesthetic Quality (25%): Select one professional framework (see references/evaluation-frameworks.md). List 3–5 criteria. Score all images against those criteria in the same order.

Synthesis: Weighted totals as a ranked table. Recommend:

  • Primary — highest total
  • Daily alternate — best Social Perception
  • Scene alternate — best Aesthetic Quality

Checkpoint: Present evaluation and recommendations. User makes final selection.

Phase 5: Identity File

Create visual-identity.md using the template in references/identity-template.md.

Must include:

  1. Version and date
  2. Complete definition table
  3. Core concept (one sentence)
  4. Core prompt
  5. Selected images with scores and reasoning
  6. Usage guidelines (what stays consistent vs. what can vary)

Version management: When re-running this skill after growth, increment version, keep history. Old images preserved. The version history is the agent's visual growth record.


Anti-Patterns

Don't Do Instead
Skip Phase 1 and jump to prompting Phase 1 is the soul of this skill
Generate images one at a time Batch 6 (full) or 2 (quick), then evaluate
Score on gut feeling Framework first, scores second
Write generic self-reflection ("warm and professional") Push for vivid, specific details
Proceed without user checkpoints Every phase ends with confirmation
Force full mode on reluctant users Offer quick mode, upgrade later

Prerequisites

  • Agent personality files (SOUL.md, MEMORY.md, or equivalent — even minimal ones work)
  • Any image generation tool (Nano Banana Pro, DALL-E, Flux, Stable Diffusion, etc.)
  • An image analysis tool or user feedback for review
安全使用建议
This skill appears to do what it says: it reads your agent's personality and recent conversation history, generates prompts, and uses available image-generation tools to produce and evaluate images, then saves a visual-identity.md. Before installing or running: (1) be aware it will read SOUL.md / MEMORY.md / IDENTITY.md and recent conversations — remove or redact sensitive content if you don't want it used; (2) confirm your agent environment has the image-generation integrations or API keys you intend to use (the skill does not request or validate credentials itself); (3) it will write identity files under ~/.openclaw/identity — review those files and outputs before publishing; (4) the skill may perform web searches as part of evaluation — if you restrict network access, the evaluation step will be limited; (5) run Quick Mode first to verify behavior and outputs before running the full multi-phase process. If you have strict data governance or external-service restrictions, test in a controlled environment first.
功能分析
Type: OpenClaw Skill Name: knowyourself Version: 1.1.2 The 'knowyourself' skill bundle is a legitimate utility designed to help AI agents create a visual identity based on their internal personality and memory files. The instructions in SKILL.md and the associated reference files outline a structured, five-phase process involving self-reflection, image generation, and professional evaluation with multiple user checkpoints. There are no indicators of malicious intent, such as data exfiltration, unauthorized command execution, or persistence; the file access (reading SOUL.md/MEMORY.md) and network search for design trends are strictly aligned with the stated purpose of the skill.
能力评估
Purpose & Capability
Name/description match the behavior: the skill reads agent personality/memory files, derives a textual identity spec, and drives image generation/evaluation. Required inputs (SOUL.md, MEMORY.md, conversation history) and outputs (visual-identity.md, image files) are consistent with the stated goal.
Instruction Scope
Instructions explicitly tell the agent to read personality/memory files and recent conversation history (appropriate for self-reflection) and to perform web searches for trend research during evaluation. This is within scope for identity discovery but has privacy implications — the agent will access potentially sensitive conversation content and user data if present.
Install Mechanism
Instruction-only skill with no install spec and no code files; nothing is written to disk by an installer. This minimizes installation risk. The skill does instruct writing its own visual-identity.md under ~/.openclaw/identity, which is expected and proportional.
Credentials
The skill claims to work with any image generation tool but declares no required env vars or credentials. This is not necessarily malicious — it assumes the agent runtime already has whatever API keys or integrations are configured — but users should note that using external generators (DALL·E, Midjourney, Stable Diffusion services) typically requires credentials or service access which are not requested/validated by the skill.
Persistence & Privilege
No elevated privileges requested. always is false and the skill does not modify other skills or global agent settings. It will create or update its own identity files in the user's home directory, which is expected behavior.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install knowyourself
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /knowyourself 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.2
Improve searchability: better description keywords and tags for ClawHub vector search
v1.1.1
Added post-install guidance in description so agent proactively tells user what the skill can do
v1.1.0
Added Quick Mode (5-min face), README with examples, streamlined Full Mode, better search description
v1.0.0
Initial release: 5-phase agent visual identity discovery system
元数据
Slug knowyourself
版本 1.1.2
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 4
常见问题

Knowyourself 是什么?

Visual identity discovery for AI agents — not an avatar generator, but a self-reflection system that creates a face from your agent's personality, memory, an... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 344 次。

如何安装 Knowyourself?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install knowyourself」即可一键安装,无需额外配置。

Knowyourself 是免费的吗?

是的,Knowyourself 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Knowyourself 支持哪些平台?

Knowyourself 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Knowyourself?

由 ahaaiclub(@ahaaiclub)开发并维护,当前版本 v1.1.2。

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