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Attestation Root Diversity Analyzer

作者 andyxinweiminicloud · GitHub ↗ · v1.0.0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install attestation-root-diversity-analyzer
功能描述
Helps measure the concentration of trust roots in a skill's attestation graph — identifying monoculture risk where a single compromised root invalidates an e...
使用说明 (SKILL.md)

\r \r

The Attestation Chain Has Seven Links. They All Trace Back to One Root.\r

\r

Helps identify when a skill's trust chain is structurally fragile — not because individual links are weak, but because all paths converge on a single root that one compromise can invalidate.\r \r

Problem\r

\r A skill with five attestation badges looks more trustworthy than a skill with one. But if four of those five badges trace back through the same root attestor, the effective trust diversity is closer to two than to five. The appearance of multiple independent validators is real; the independence is not.\r \r This is a topology problem, not a cryptography problem. A trust graph where all paths converge on a single root is not a distributed trust system — it's a hub-and-spoke system wearing the visual appearance of a mesh. A hub-and-spoke system has all the failure properties of centralized trust: compromise the hub, and every spoke-rooted badge becomes invalid simultaneously.\r \r The risk is not hypothetical. Self-attesting roots — where the publisher is also the root attestor, or where multiple attestation badges trace back to a single organization — are common in ecosystems where attestation is new and infrastructure is thin. A skill from a well-known publisher that has also reviewed its own dependencies through affiliated validators presents structural fragility even if every individual attestation is cryptographically correct.\r \r Measuring this requires looking at the full trust graph, not just the badges at the leaves.\r \r

What This Analyzes\r

\r This analyzer examines attestation root diversity across five dimensions:\r \r

  1. Root concentration index — What fraction of the attestation graph's trust paths converge on each distinct root? A Herfindahl-style concentration measure identifies whether trust is effectively distributed or structurally centralized\r
  2. Self-attestation detection — Does the skill's publisher appear anywhere in its own trust chain? Self-attestation is not inherently invalid, but it must be disclosed and weighted appropriately\r
  3. Organizational diversity — Are the distinct roots associated with independent organizations, or do multiple roots trace back to the same controlling entity through different organizational names?\r
  4. Effective validator count — After accounting for convergence, how many truly independent validators contribute to the skill's trust score? A skill with 12 badges from 3 organizations has an effective count of 3, not 12\r
  5. Structural fragility score — If the highest-concentration root were compromised, what percentage of the skill's attestation graph would be invalidated?\r \r

How to Use\r

\r Input: Provide one of:\r

  • A skill identifier with its attestation metadata\r
  • A trust graph (validator chain, root identifiers) to analyze\r
  • Two skills to compare relative root concentration\r \r Output: A root diversity report containing:\r
  • Root concentration index (0 = fully distributed, 1 = single root)\r
  • Attestation graph visualization (text-based)\r
  • Self-attestation flags\r
  • Organizational diversity assessment\r
  • Effective validator count\r
  • Structural fragility score\r
  • Diversity verdict: DISTRIBUTED / CONCENTRATED / MONOCULTURE / SELF-ATTESTING\r \r

Example\r

\r Input: Analyze attestation root diversity for workflow-automator skill\r \r

🌐 ATTESTATION ROOT DIVERSITY ANALYSIS\r
\r
Skill: workflow-automator\r
Attestation badges: 7\r
Audit timestamp: 2025-04-20T14:00:00Z\r
\r
Trust graph structure:\r
  Badge A → Validator-1 → Root-Alpha (publisher-org)\r
  Badge B → Validator-2 → Root-Alpha (publisher-org)\r
  Badge C → Validator-3 → Root-Alpha (publisher-org)\r
  Badge D → Validator-4 → Root-Beta (third-party)\r
  Badge E → Validator-5 → Root-Beta (third-party)\r
  Badge F → Validator-6 → Root-Alpha (publisher-org)  ← affiliate\r
  Badge G → Validator-7 → Root-Gamma (community)\r
\r
Root concentration analysis:\r
  Root-Alpha (publisher-org): 4/7 paths (57%) → publisher + 3 affiliated validators\r
  Root-Beta (third-party): 2/7 paths (29%)\r
  Root-Gamma (community): 1/7 paths (14%)\r
\r
Herfindahl index: 0.57² + 0.29² + 0.14² = 0.42\r
  (0 = perfect distribution, 1 = single root)\r
  Classification: CONCENTRATED (threshold: >0.33 = concentrated)\r
\r
Self-attestation: ⚠️ DETECTED\r
  Root-Alpha is publisher-org — publisher attests to its own skill\r
  3 of 7 badges trace directly to publisher-controlled validators\r
\r
Organizational diversity:\r
  Distinct organizations: 3 (publisher-org, third-party, community)\r
  Effective independent: 2 (publisher-org counts as 1 despite 4 paths)\r
  Effective validator count: 2.4 (weighted by independence)\r
\r
Structural fragility:\r
  If Root-Alpha were compromised: 4/7 badges (57%) invalidated\r
  Residual trust: Root-Beta (29%) + Root-Gamma (14%) = 43%\r
\r
Diversity verdict: CONCENTRATED\r
  7 badges with 3 roots, but effective independence is 2.4 validators.\r
  Root-Alpha concentration exceeds recommended threshold for high-impact\r
  skills. Self-attestation by publisher reduces independence further.\r
\r
Recommended actions:\r
  1. Require minimum 2 non-publisher roots for full DISTRIBUTED status\r
  2. Disclose self-attestation presence in badge display\r
  3. Weight Root-Alpha badges at 0.5× for concentration-aware scoring\r
  4. Target Root-Gamma growth to reduce Alpha concentration below 0.33\r
```\r
\r
## Related Tools\r
\r
- **attestation-chain-auditor** — Validates chain integrity and completeness; root diversity analyzer measures whether that chain's roots are structurally independent\r
- **transparency-log-auditor** — Checks whether signing events are independently auditable; diverse roots are more valuable when each root's behavior is logged\r
- **publisher-identity-verifier** — Verifies publisher identity; publisher as self-attesting root is a specific concentration risk to flag\r
- **trust-velocity-calculator** — Quantifies trust decay rate; concentrated attestation graphs decay faster when a root is compromised\r
\r
## Limitations\r
\r
Root diversity analysis requires access to the full attestation graph, including the organizational relationships between validators — data that many current marketplaces do not expose. Where only the leaf badges are visible and root relationships must be inferred, the analysis is necessarily approximate. Organizational independence is difficult to verify programmatically: two organizations with different names may share effective control. The Herfindahl-based concentration measure is a useful heuristic, not a definitive security assessment — the appropriate threshold depends on the risk profile of the capability being attested. A concentrated attestation graph is a structural concern, not a confirmation of compromise; it means the trust infrastructure is more fragile, not that it has already failed.\r
安全使用建议
This skill looks internally consistent: it analyzes attestation graphs and reasonably needs curl/python3 to fetch and process metadata. Before installing, consider: 1) Source provenance — the skill's source/homepage is unknown; prefer skills with a traceable source. 2) Network fetches — the skill implies using curl to pull attestation data; confirm which endpoints the agent will query and run it in a network-isolated environment if you have strict policies. 3) Private attestations — the skill does not request credentials; if you supply private attestation data or credentials to analyze private graphs, do so only after verifying the environment. 4) Autonomy — the skill can be invoked by the agent automatically (platform default), so check agent policies if you want to restrict autonomous network access. If you want higher assurance, ask the publisher for a sample of the exact curl/python commands or a small vetted parser implementation before enabling the skill in production.
功能分析
Type: OpenClaw Skill Name: attestation-root-diversity-analyzer Version: 1.0.0 The provided files consist solely of metadata and documentation for a skill designed to analyze attestation root diversity. The `SKILL.md` requests common binaries (`curl`, `python3`) and describes a legitimate security analysis function without any evidence of malicious intent, prompt injection attempts, or risky behaviors. No executable code was provided for deeper analysis, but the descriptive content is benign.
能力评估
Purpose & Capability
The skill's name and description match the operations described in SKILL.md: parsing attestation graphs, computing concentration metrics, and producing a diversity verdict. Required binaries (curl, python3) are reasonable for fetching and processing attestation metadata. No unrelated credentials, config paths, or heavy dependencies are requested.
Instruction Scope
SKILL.md is focused on analyzing trust graphs and gives examples; it does not instruct the agent to read arbitrary local files or secret env vars. However, because the skill is instruction-only and lists curl/python3 as required, the runtime behavior implies network fetches of attestation metadata (via curl) and local processing (via python3). The SKILL.md does not enumerate specific endpoints to contact or include code, so you should expect the agent to fetch whatever URLs are supplied by user input or discovered from the skill registry.
Install Mechanism
There is no install spec and no code files. This is the lowest-risk form: nothing is written to disk by an installer. The skill relies on existing system binaries only.
Credentials
The skill declares no environment variables, no credentials, and no config paths. That is proportionate to its stated purpose. If you plan to analyze attestations that are behind authenticated endpoints, those credentials would need to be provided externally (the skill does not request them).
Persistence & Privilege
always is false and the skill does not request persistent system changes or privileges. Autonomous invocation is allowed (platform default), which is appropriate for a tool that performs analyses on demand.
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 attestation-root-diversity-analyzer
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /attestation-root-diversity-analyzer 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
v1.0.0
Attestation Root Diversity Analyzer 1.0.0 - Initial release of the attestation root diversity analyzer. - Analyzes skill attestation graphs to assess root concentration and monoculture risk. - Reports on five dimensions: root concentration index, self-attestation, organizational diversity, effective validator count, and structural fragility. - Provides clear verdicts (DISTRIBUTED, CONCENTRATED, MONOCULTURE, SELF-ATTESTING) and actionable recommendations. - Designed to highlight concealed centralization and improve trust transparency in skill ecosystems.
元数据
Slug attestation-root-diversity-analyzer
版本 1.0.0
许可证
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Attestation Root Diversity Analyzer 是什么?

Helps measure the concentration of trust roots in a skill's attestation graph — identifying monoculture risk where a single compromised root invalidates an e... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 434 次。

如何安装 Attestation Root Diversity Analyzer?

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

Attestation Root Diversity Analyzer 是免费的吗?

是的,Attestation Root Diversity Analyzer 完全免费(开源免费),可自由下载、安装和使用。

Attestation Root Diversity Analyzer 支持哪些平台?

Attestation Root Diversity Analyzer 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 Attestation Root Diversity Analyzer?

由 andyxinweiminicloud(@andyxinweiminicloud)开发并维护,当前版本 v1.0.0。

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