Skills entity-optimizer

📦

entity-optimizer

Name: entity-optimizer
Author: aaron-he-zhu

v17.0.0 Content revision r1 Safe 📁 Filesystem access⚙️ External commands🌐 Network access

Optimize Knowledge Graph Entity Presence

Inconsistent entity facts weaken search and AI recognition. This skill audits evidence, resolves identity conflicts, and records authorized canonical updates with provenance.

Supports: Claude Codex Code(CC)

🥉 78 Bronze

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "entity-optimizer" from https://skillstore.io/skills/aaron-he-zhu-entity-optimizer.md and its manifest at https://skillstore.io/api/skills/aaron-he-zhu-entity-optimizer/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/aaron-he-zhu-entity-optimizer.md Signed manifest GET /api/skills/aaron-he-zhu-entity-optimizer/manifest Signed lockfile GET /api/skills/aaron-he-zhu-entity-optimizer/lockfile

Test it

Using "entity-optimizer". Audit Acme Analytics using its official domain and verified LinkedIn profile.

Expected outcome:

Structured data: Partial. The organization type is present, but sameAs evidence is incomplete.
Knowledge bases: Unknown. No verified QID was supplied.
Priority action: Verify external identifiers before proposing a canonical update.

Using "entity-optimizer". Explain why two products named Atlas are being confused.

Expected outcome:

The records share a name but lack verified cross-links. Keep separate IDs and add domain, product category, and official profile evidence.

Using "entity-optimizer". Review pending changes for entity-7f42.

Expected outcome:

Proposal review: One fact has current evidence and matching revision context.
Open conflict: Two same-date sources disagree on the canonical domain.
Decision: Leave the conflicting proposal pending until the owner confirms the domain.

Security Audit

Safe

v6 • 7/12/2026 Open versioned report

All 36 static findings are false positives caused by Markdown formatting, documentation links, metadata URLs, or bounded commands with fixed executables and quoted arguments. No prompt injection, credential exposure, unsafe dynamic execution, or malicious data-handling intent was found.

Files scanned

447

Lines analyzed

Review items

False positives ignored

Risk Factors

📁 Filesystem access (14)

references/entity-signal-checklist.md:3 SKILL.md:38 SKILL.md:39 SKILL.md:44 SKILL.md:67 SKILL.md:87 SKILL.md:88 SKILL.md:92 SKILL.md:96 SKILL.md:97 SKILL.md:98 SKILL.md:99 SKILL.md:100 SKILL.md:67

⚙️ External commands (16)

SKILL.md:22-27 SKILL.md:27-31 SKILL.md:31 SKILL.md:33 SKILL.md:40 SKILL.md:50-55 SKILL.md:55-67 SKILL.md:67-69 SKILL.md:69-72 SKILL.md:72 SKILL.md:73 SKILL.md:74-75 SKILL.md:75-77 SKILL.md:77 SKILL.md:67 SKILL.md:67

🌐 Network access (2)

SKILL.md:10 SKILL.md:13

No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.

Audited by: codex View Audit History →

Share & cite this report

Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.

Open versioned report

Copy report link

https://skillstore.io/skills/aaron-he-zhu-entity-optimizer/audits/6?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

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Academic citations (APA · BibTeX · CFF)

APA citation

aaron-he-zhu. (2026). entity-optimizer security audit report (audit version 6) [Author version 17.0.0]. Skillstore. https://skillstore.io/skills/aaron-he-zhu-entity-optimizer/audits/6

BibTeX citation

@techreport{aaron-he-zhu-aaron-he-zhu-entity-optimizer-2026,
  author = {aaron-he-zhu},
  title = {entity-optimizer security audit report (audit version 6)},
  institution = {Skillstore},
  year = {2026},
  number = {6},
  url = {https://skillstore.io/skills/aaron-he-zhu-entity-optimizer/audits/6},
  note = {Author version 17.0.0}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "entity-optimizer security audit report (audit version 6)"
version: "17.0.0"
type: report
authors:
  - name: "aaron-he-zhu"
date-released: "2026-07-12"
url: "https://skillstore.io/skills/aaron-he-zhu-entity-optimizer/audits/6"
identifiers:
  - type: other
    value: "skillstore:aaron-he-zhu-entity-optimizer:audit:6"
    description: "Skillstore immutable audit report identifier"

Skillstore Score

Why this score Evidence Confidence: Medium

Architecture

100

Maintainability

Content

Community

Spec Compliance

What You Can Build

Audit an organization

Assess machine-facing identity signals and prioritize evidence-backed corrections across owned and authoritative sources.

Reconcile registry proposals

Review proposed facts, resolve duplicate identifiers, and preserve conflicting evidence before authorized acceptance.

Diagnose AI confusion

Compare entity descriptions and associations to identify why AI systems confuse similar organizations or products.

Try These Prompts

Run a basic entity audit

Audit entity recognition for [entity name]. Use [official domain] and these verified profiles: [links]. Mark unavailable checks as unknown.

Check identity consistency

Compare the canonical name, type, domain, schema @id, QID, and sameAs links for [entity]. Report conflicts and missing evidence.

Resolve ambiguous entities

Disambiguate [entity A] from [entity B]. Require verified cross-links, preserve conflicting evidence, and propose changes without writing them.

Adjudicate registry proposals

Review pending proposals for [aggregate ID] in offset order. Validate provenance, revision expectations, authority, and downstream dependencies before recommending decisions.

Best Practices

Use primary sources, record observation dates, and preserve provenance for every factual claim.
Require verified cross-links or explicit confirmation before merging similar entities.
Ask before persistent writes and keep capability values out of prompts, files, and logs.