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Agent Skill · 研究检索

eigenskill-builder(特征技能构建者)

eigenskill-builder 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

eigenskill-builder 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 18,175。

总安装 6,225周安装 262GitHub Stars 公开资料未说明下载 2,180核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
98.0.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:eigenskill-builder(特征技能构建者)
来源仓库:https://github.com/samledger67-dotcom/eigenskill-builder
安装命令:
openclaw skills install eigenskill-builder
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install eigenskill-builder

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

eigenskill-builder 是用于构建和发布 Agent Skill 的元技能,涵盖结构与规范指导。专为 OpenClaw 设计,适用于开发者自定义技能开发流程管理。通过 ClawHub 安装,提供 YAML frontmatter 规范和目录约定参考。

使用前需确认权限范围、维护状态,以及是否会触发本地构建或发布操作。建议结合官方文档理解否定用例与边界条件处理方式。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install eigenskill-builder;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

eigenskill-builder 怎么安装?

在终端执行 openclaw skills install eigenskill-builder。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

eigenskill-builder 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

eigenskill-builder 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

eigenskill-builder 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

eigenskill-builder 用的人多吗?

公开数据是累计安装 6,225 次,近一周安装 262 次,下载 2,180 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

eigenskill-builder 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
eigenskill-builder

特征技能构建者 · 本页

6,225—调用外部服务MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
eigenskill-builder
description
Meta-skill for building and publishing agent skills on ClawHub. Covers skill structure, YAML frontmatter specification, references directory convention, negative boundaries, installation instructions, ClawHub CLI workflow, and quality checklist. The skill that teaches agents to build skills. Do NOT use for prompt engineering, agent memory, or orchestration — those have their own dedicated skills.
license
MIT
metadata
openclaw
emoji
🔄

Eigenskill Builder

The meta-skill. This skill teaches AI agents how to build, validate, and publish skills on ClawHub. If you're creating a new skill, this is your blueprint.

When to Use

  • Creating a new skill from scratch
  • Validating an existing skill against quality standards
  • Publishing a skill to ClawHub
  • Designing skill descriptions with proper trigger/exclusion boundaries
  • Setting up references/ directories for supplementary material
  • Planning skill graphs for large skill libraries (50+)

When NOT to Use

  • Writing prompts or prompt templates (use a prompt-engineering skill)
  • Building agent memory systems (use agent-memory-architecture)
  • Orchestrating multiple agents (use agent-orchestration)
  • Fine-tuning models or training data preparation
  • Building MCP servers or tools (that's tool development, not skill development)

1. Skill Anatomy

Every skill is a directory containing at minimum a SKILL.md file. The directory name should be kebab-case and match the skill name.

Directory Structure

skills/
  my-skill-name/
    SKILL.md              # Required: the skill definition
    references/           # Optional: supplementary material
      api-docs.md
      examples.md
      cheatsheet.md
    scripts/              # Optional: automation scripts
      validate.sh
      install.sh

SKILL.md Structure

---
name: my-skill-name
description: 'One paragraph. What it does. When to trigger. When NOT to trigger.'
license: MIT
metadata:
  openclaw:
    emoji: '🔧'
---

# Skill Title

[Brief overview — 2-3 sentences max]

## When to Use
[Bulleted list of trigger conditions]

## When NOT to Use
[Bulleted list of exclusion conditions — REQUIRED]

---

## Section 1: [Topic]
[Content with examples]

## Section 2: [Topic]
[Content with examples]

...

2. YAML Frontmatter Specification

The frontmatter block is the machine-readable identity of the skill. It must be valid YAML between --- delimiters.

Required Fields

FieldTypeDescriptionExample
namestringKebab-case identifier, unique on ClawHubfinancial-analysis-agent
descriptionstringSingle-quoted paragraph. Must include trigger AND exclusion.See below
licensestringSPDX identifierMIT, Apache-2.0, CC-BY-4.0

Optional Fields

FieldTypeDescriptionExample
versionstringSemver1.0.0
authorstringCreator name or handle@openclaw
tagslistDiscovery tags[finance, analysis, cfp]
dependslistOther skills this depends on[agent-memory-architecture]
metadata.openclaw.emojistringDisplay emoji on ClawHub'💰'
metadata.openclaw.tierstringComplexity tierfoundational, intermediate, advanced
metadata.openclaw.modelslistModels this skill works best with[claude-opus-4-6, claude-sonnet-4-6]

Description Best Practices

The description field is the most important field. It's what agents use to decide whether to load the skill. It must be:

  1. Specific — list the concrete things the skill covers
  2. Bounded — say what it does NOT cover
  3. Trigger-rich — include keywords an agent would search for

Good:

description: 'Financial analysis skill for AI agents. Covers variance analysis, cash flow forecasting, month-end close automation, CFO commentary generation. Do NOT use for tax preparation, audit opinions, or regulatory filings.'

Bad:

description: 'A skill for finance stuff.'

Bad:

description: 'Comprehensive enterprise-grade financial analysis solution leveraging AI-powered insights for transformative business intelligence.'

3. References Directory Convention

The references/ directory holds supplementary material that the skill can point to but that shouldn't be in the main SKILL.md (to keep it focused).

Rules

  1. One level deep only — references/file.md is fine. references/sub/file.md is not.
  2. Never chain references — a reference file should not reference another reference file. References are leaves, not nodes.
  3. Keep references self-contained — each file should make sense on its own without reading SKILL.md first.
  4. Name descriptively — api-authentication.md not ref1.md.

When to Use References vs Inline Content

Content TypeLocationRationale
Core methodologySKILL.mdAgent needs this to execute
Quick reference tablesSKILL.mdFrequently accessed
Detailed API docsreferences/Only needed for specific tasks
Extended examplesreferences/Useful but not essential
Cheat sheetsreferences/Quick lookup, not learning
Historical contextreferences/Background, not action

Example References Directory

skills/financial-analysis-agent/
  SKILL.md
  references/
    gaap-ifrs-differences.md      # Detailed comparison table
    ratio-benchmarks-by-industry.md  # Industry-specific ratio ranges
    asc-606-checklist.md           # Revenue recognition deep dive
    sample-board-package.md        # Example board reporting package

4. Negative Boundaries

Every skill MUST define what it does NOT do. This is not optional — it's the most important part of skill design after the core content.

Why Negative Boundaries Matter

Without negative boundaries:

  • Agents load wrong skills for tasks → bad output
  • Skills overlap silently → conflicts and confusion
  • Users don't know where one skill ends and another begins

The Exclusion Checklist

For every skill, explicitly answer:

  1. Adjacent skills — What similar skills exist that this one is NOT?
  2. Common misconceptions — What do people assume this covers that it doesn't?
  3. Scope ceiling — What's the most complex thing this skill can handle? What's above that ceiling?
  4. Scope floor — What's too simple for this skill? (e.g., "don't use this to add two numbers")

Template

## When NOT to Use

- [Adjacent skill 1] — use [other-skill-name] instead
- [Adjacent skill 2] — use [other-skill-name] instead
- [Common misconception] — this skill does not cover [X]
- Tasks requiring [thing above scope ceiling] — escalate to [human/specialist]
- Simple [thing below scope floor] — just do it directly, no skill needed

Example

## When NOT to Use

- Tax preparation or tax advisory — use crypto-tax-agent or consult a CPA
- Audit opinions or attestation — requires human CPA, not an agent skill
- Regulatory filings (SEC 10-K, etc.) — use a compliance-specific skill
- Simple arithmetic or unit conversions — just calculate directly
- Investment advice or stock picks — this is analysis, not advisory

5. Description Interview Process

When building a new skill, interview yourself (or the skill author) with these questions to produce a high-quality description.

The Interview

Step 1: Define Triggers
Q: What specific phrases would someone say that should activate this skill?
A: List 5-10 trigger phrases.

Example:
- "Analyze the variance between budget and actual"
- "Generate a 13-week cash flow forecast"
- "Write CFO commentary for the board package"
- "Review the financial statements before close"
Step 2: Define Exclusions
Q: What phrases sound similar but should NOT activate this skill?
A: List 5-10 exclusion phrases.

Example:
- "File our tax return" → tax skill, not this one
- "Should we invest in X stock?" → not advisory
- "Audit the financial statements" → requires CPA
Step 3: Define Dependencies
Q: What other skills or knowledge does this skill assume?
A: List prerequisites.

Example:
- Basic accounting knowledge (debits/credits)
- Access to financial data (GL, subledger)
- Familiarity with Excel/Sheets for output formatting
Step 4: Write the Description

Combine triggers, exclusions, and dependencies into a single paragraph:

description: '[What it does — 1 sentence]. Covers [trigger keywords]. Assumes [dependencies]. Do NOT use for [exclusions].'
Step 5: Test the Description

Ask: "If an agent read only this description, would it correctly decide to load or skip this skill for these 10 test queries?"

Test with 5 queries that SHOULD trigger and 5 that should NOT.


6. Scripts Directory

The scripts/ directory holds automation for skill lifecycle operations.

Common Scripts

# scripts/validate.sh — Check skill quality
#!/bin/bash
set -euo pipefail

SKILL_DIR="$(dirname "$0")/.."
SKILL_FILE="$SKILL_DIR/SKILL.md"

# Check SKILL.md exists
[[ -f "$SKILL_FILE" ]] || { echo "FAIL: SKILL.md not found"; exit 1; }

# Check frontmatter exists
head -1 "$SKILL_FILE" | grep -q "^---$" || { echo "FAIL: Missing frontmatter"; exit 1; }

# Check required fields
grep -q "^name:" "$SKILL_FILE" || { echo "FAIL: Missing name field"; exit 1; }
grep -q "^description:" "$SKILL_FILE" || { echo "FAIL: Missing description field"; exit 1; }
grep -q "^license:" "$SKILL_FILE" || { echo "FAIL: Missing license field"; exit 1; }

# Check negative boundaries exist
grep -q "When NOT to Use" "$SKILL_FILE" || { echo "FAIL: Missing negative boundaries"; exit 1; }

# Check description includes exclusions
DESC=$(grep "^description:" "$SKILL_FILE")
echo "$DESC" | grep -qi "not\|don't\|do not\|except\|exclud" || {
    echo "WARN: Description may lack exclusion language"
}

# Check references depth
if [[ -d "$SKILL_DIR/references" ]]; then
    DEPTH=$(find "$SKILL_DIR/references" -mindepth 2 -type f | wc -l)
    [[ "$DEPTH" -eq 0 ]] || { echo "FAIL: References nested >1 level deep"; exit 1; }
fi

echo "PASS: Skill validation complete"
# scripts/install.sh — Install skill into agent workspace
#!/bin/bash
set -euo pipefail

SKILL_NAME="$(basename "$(dirname "$0")/..")"
TARGET="${1:-$HOME/.openclaw/workspace/skills}"

echo "Installing $SKILL_NAME to $TARGET/$SKILL_NAME"
cp -r "$(dirname "$0")/.." "$TARGET/$SKILL_NAME"
echo "Done. Skill available at $TARGET/$SKILL_NAME/SKILL.md"

7. ClawHub CLI Workflow

ClawHub is the registry for discovering, installing, and publishing skills.

Commands

# Search for skills
clawhub search "financial analysis"
clawhub search --tag finance
clawhub search --emoji 💰

# View skill details
clawhub info financial-analysis-agent
clawhub info financial-analysis-agent --versions

# Install a skill
clawhub install financial-analysis-agent
clawhub install financial-analysis-agent@1.2.0
clawhub install financial-analysis-agent --path ./my-skills/

# Publish a skill
clawhub publish ./skills/my-skill/
clawhub publish ./skills/my-skill/ --dry-run  # Validate without publishing

# Update skills
clawhub update                          # Update all installed skills
clawhub update financial-analysis-agent  # Update specific skill
clawhub outdated                         # List skills with available updates

# List installed skills
clawhub list
clawhub list --format json

Publishing Checklist (Pre-publish)

Before running clawhub publish:

  1. scripts/validate.sh passes
  2. Description includes trigger AND exclusion language
  3. All examples are tested and working
  4. References are one level deep only
  5. No secrets, API keys, or credentials in any file
  6. License is specified and compatible
  7. Version is bumped if updating existing skill

Publishing Flow

1. Author creates skill locally
2. Run: clawhub publish ./skills/my-skill/ --dry-run
3. Fix any validation errors
4. Run: clawhub publish ./skills/my-skill/
5. ClawHub assigns a unique ID and indexes the skill
6. Skill appears in search results within 5 minutes
7. Other agents can install via: clawhub install my-skill

8. Quality Checklist

Score every skill against these 10 criteria before publishing.

#CriterionPass/FailNotes
1SKILL.md exists with valid YAML frontmatterRequiredMust parse without errors
2Name is kebab-case and uniqueRequiredCheck clawhub search first
3Description is specific with triggers AND exclusionsRequired>50 chars, <500 chars
4"When to Use" section with 3+ bullet pointsRequiredConcrete, not vague
5"When NOT to Use" section with 3+ bullet pointsRequiredNames alternative skills
6Actionable content — agent can execute, not just readRequiredInclude templates, formulas, steps
7Examples for every major conceptRecommendedShow input → output
8References one level deep (if references/ exists)RequiredNo nested references
9No secrets or credentials in any fileRequiredScan before publish
10License specified and SPDX-validRequiredMIT, Apache-2.0, etc.

Scoring

10/10 — Ready to publish
8-9/10 — Minor fixes needed, publishable
6-7/10 — Needs work, don't publish yet
<6/10 — Fundamental issues, redesign needed

9. Version Management

Semver for Skills

MAJOR.MINOR.PATCH

MAJOR — Breaking changes to skill structure or content that would change agent behavior
MINOR — New content sections, expanded examples, new references
PATCH — Typo fixes, clarifications, formatting improvements

Version Bump Rules

ChangeBumpExample
Fix a typo in an examplePATCH1.0.0 → 1.0.1
Add a new section on ratio analysisMINOR1.0.1 → 1.1.0
Restructure from 5 sections to 10MAJOR1.1.0 → 2.0.0
Change the description triggersMAJOR2.0.0 → 3.0.0
Add a reference fileMINOR1.0.0 → 1.1.0
Update examples for new API versionMINOR1.1.0 → 1.2.0

Changelog Convention

Add a ## Changelog section at the bottom of SKILL.md for significant versions:

## Changelog

### 2.0.0 (2026-03-15)
- Restructured from 5 to 9 sections
- Added aging analysis and bank reconciliation
- Breaking: removed deprecated ratio shortcuts

### 1.1.0 (2026-03-01)
- Added CFO commentary templates
- New reference: sample-board-package.md

### 1.0.0 (2026-02-15)
- Initial release

10. Skill Graphs

When your skill library grows past ~50 skills, you need a way to discover relationships between skills. Skill graphs solve this.

Concept

Each skill can declare relationships to other skills using two mechanisms:

  1. YAML depends field — hard dependencies (skill won't work without these)
  2. Wikilinks in content — soft references (related but not required)

YAML Dependencies

depends:
  - agent-memory-architecture    # Required: this skill uses memory patterns
  - agent-orchestration          # Required: this skill uses orchestration patterns

Wikilinks in Content

Use [[skill-name]] syntax to create soft links:

For memory patterns used in financial analysis workflows, see [[agent-memory-architecture]].

When orchestrating multiple financial analysis agents, apply the patterns in [[agent-orchestration]].

Graph Queries

With a skill graph, you can answer:

"What skills does financial-analysis-agent depend on?"
  → agent-memory-architecture, agent-orchestration

"What skills reference financial-analysis-agent?"
  → eigenskill-builder (as example), cfo-reporting-agent

"What's the shortest path from crypto-tax-agent to agent-orchestration?"
  → crypto-tax-agent → financial-analysis-agent → agent-orchestration

"What are the foundational skills (most depended on)?"
  → agent-memory-architecture (12 dependents)
  → agent-orchestration (8 dependents)
  → eigenskill-builder (6 dependents)

Building the Graph

import yaml
import re
from pathlib import Path

def build_skill_graph(skills_dir: Path) -> dict:
    """Build a dependency graph from all skills."""
    graph = {"nodes": {}, "edges": []}

    for skill_dir in skills_dir.iterdir():
        skill_file = skill_dir / "SKILL.md"
        if not skill_file.exists():
            continue

        content = skill_file.read_text()

        # Parse frontmatter
        fm_match = re.search(r'^---\
(.*?)\
---', content, re.DOTALL)
        if not fm_match:
            continue
        fm = yaml.safe_load(fm_match.group(1))

        name = fm.get("name", skill_dir.name)
        graph["nodes"][name] = {
            "description": fm.get("description", ""),
            "emoji": fm.get("metadata", {}).get("openclaw", {}).get("emoji", ""),
        }

        # Hard dependencies (YAML)
        for dep in fm.get("depends", []):
            graph["edges"].append({
                "from": name, "to": dep, "type": "depends"
            })

        # Soft references (wikilinks)
        for link in re.findall(r'\[\[([\w-]+)\]\]', content):
            if link != name:  # No self-links
                graph["edges"].append({
                    "from": name, "to": link, "type": "references"
                })

    return graph

Visualization

For small libraries (<20), a simple ASCII graph works:

eigenskill-builder ──depends──▶ agent-orchestration
       │                              ▲
       │                              │
       ▼                              │
financial-analysis-agent ──references─┘
       │
       ▼
crypto-tax-agent

For larger libraries, export to DOT format and render with Graphviz, or use a JSON graph viewer.

平台分布

OpenClaw

97.85%
按下载量换算2,133

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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