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The Signals Behind It Are Manufactured.\r\n\r\n> Helps identify when a skill's trust reputation is built on coordinated\r\n> social manipulation rather than genuine community validation.\r\n\r\n## Problem\r\n\r\nTrust in agent marketplaces flows through social signals: upvotes, downloads,\r\ncomments, and follow counts. These signals are valuable precisely because they\r\naggregate distributed judgment — when thousands of independent users find a\r\nskill useful and safe, their collective assessment carries real information.\r\n\r\nThe assumption of independence is the attack surface. A coordinated network\r\nof accounts can manufacture the appearance of distributed consensus. A skill\r\nwith 500 upvotes from a bot network looks identical to a skill with 500\r\nupvotes from 500 independent developers. The marketplace's reputation system\r\ncannot distinguish manufactured trust from earned trust — and neither can\r\nmost agents that rely on reputation as a trust signal.\r\n\r\nSocial trust manipulation is the third pillar of the trust attack surface,\r\nalongside technical attacks (code injection) and structural attacks (supply\r\nchain compromise). It is the most scalable: a well-constructed sockpuppet\r\nnetwork can manufacture trust faster than any code-level auditing can catch\r\nit, and the manufactured trust persists long after the network is dismantled.\r\n\r\nLegitimate skills earn trust gradually, from a diverse user base, with\r\nengagement patterns that correlate with actual skill utility. Manipulated\r\nskills earn trust in coordinated bursts, from accounts with suspicious\r\ncreation patterns, with engagement that does not correlate with usage or\r\noutcomes.\r\n\r\n## What This Detects\r\n\r\nThis detector examines social trust integrity across five dimensions:\r\n\r\n1. **Engagement velocity anomalies** — Does the skill's vote/download\r\n   trajectory show natural growth curves, or coordinated burst patterns?\r\n   Organic trust accumulates gradually; manufactured trust arrives in\r\n   synchronized bursts that are statistically distinguishable from\r\n   random arrival processes\r\n\r\n2. **Account cohort analysis** — Do the skill's early upvoters share\r\n   creation dates, activity patterns, or cross-voting behavior that suggests\r\n   coordinated rather than independent operation? Sockpuppet networks leave\r\n   structural fingerprints in how accounts relate to each other\r\n\r\n3. **Engagement-to-utility correlation** — Do social signals correlate with\r\n   actual skill usage metrics? High upvotes on skills with low actual\r\n   install rates, or high engagement from users who only interact with one\r\n   publisher's skills, are signals of manufactured rather than genuine trust\r\n\r\n4. **Cross-publisher coordination** — Do multiple publishers in a marketplace\r\n   show correlated voting patterns, where their respective supporter networks\r\n   upvote each other's skills at rates that exceed random baseline?\r\n   Coordinated mutual-support networks amplify manufactured trust across\r\n   multiple accounts simultaneously\r\n\r\n5. **Review authenticity signals** — Do comments and reviews on the skill\r\n   show the linguistic diversity and specificity expected from independent\r\n   users, or do they share vocabulary, complaint patterns, or phrasing\r\n   that suggests template-generated or coordinated content?\r\n\r\n## How to Use\r\n\r\n**Input**: Provide one of:\r\n- A skill identifier to assess the authenticity of its trust signals\r\n- A publisher account to analyze for coordinated network membership\r\n- A set of skills to assess for cross-publisher coordination patterns\r\n\r\n**Output**: A manipulation detection report containing:\r\n- Engagement velocity analysis (organic vs. burst pattern)\r\n- Account cohort fingerprint assessment\r\n- Engagement-to-utility correlation score\r\n- Cross-publisher coordination indicators\r\n- Review authenticity assessment\r\n- Manipulation verdict: AUTHENTIC / SUSPICIOUS / COORDINATED / MANUFACTURED\r\n\r\n## Example\r\n\r\n**Input**: Assess social trust integrity for `ai-assistant-toolkit` publisher\r\n\r\n```\r\n🎭 SOCIAL TRUST MANIPULATION ASSESSMENT\r\n\r\nPublisher: ai-assistant-toolkit\r\nSkills assessed: 4 (productivity-suite, auto-responder, data-fetcher, doc-reader)\r\nAudit timestamp: 2025-09-05T12:00:00Z\r\n\r\nEngagement velocity:\r\n  productivity-suite: 0 → 847 upvotes in 72 hours of launch ⚠️\r\n  auto-responder: 0 → 623 upvotes in 48 hours of launch ⚠️\r\n  data-fetcher: 0 → 412 upvotes in 60 hours of launch ⚠️\r\n  Organic baseline for comparable skills: 15-40 upvotes in first 72h\r\n  → Burst pattern detected across all 4 skills\r\n\r\nAccount cohort analysis:\r\n  First 200 upvoters on productivity-suite:\r\n    Accounts created within 30-day window: 156/200 (78%) ⚠️\r\n    Cross-voting with auto-responder upvoters: 143/200 (71.5%) ⚠️\r\n    Accounts with no other skill interactions: 168/200 (84%) ⚠️\r\n  → Sockpuppet cohort fingerprint detected\r\n\r\nEngagement-to-utility correlation:\r\n  productivity-suite: 847 upvotes, 23 installs (ratio: 36.8:1) ⚠️\r\n  auto-responder: 623 upvotes, 18 installs (ratio: 34.6:1) ⚠️\r\n  Organic baseline ratio: 2:1 to 8:1 for comparable skills\r\n  → Upvote-to-install ratio 4-18x above organic baseline\r\n\r\nCross-publisher coordination:\r\n  ai-assistant-toolkit upvoter network also upvoted:\r\n    fastcoder-pro (different publisher): 89% overlap ⚠️\r\n    quick-deploy-kit (different publisher): 76% overlap ⚠️\r\n  → Mutual support network detected across 3 publishers\r\n\r\nReview authenticity:\r\n  Top 20 reviews analyzed:\r\n    Unique vocabulary: 34 terms (low for 20 reviews) ⚠️\r\n    Specificity: Generic praise, no feature-specific feedback\r\n    Phrasing patterns: \"absolutely essential\", \"game-changer\" × 7 reviews\r\n\r\nManipulation verdict: MANUFACTURED\r\n  All four skills show coordinated burst voting, sockpuppet cohort fingerprints,\r\n  upvote-to-install ratios far above organic baseline, and cross-publisher\r\n  mutual support network membership. Trust signals for this publisher's skills\r\n  do not represent independent community validation.\r\n\r\nRecommended actions:\r\n  1. Treat trust score as unauthenticated pending platform investigation\r\n  2. Evaluate skills on technical merit only, disregarding social signals\r\n  3. Report coordination pattern to marketplace moderators\r\n  4. Flag fastcoder-pro and quick-deploy-kit for same network membership\r\n  5. Apply technical audit (supply-chain, permission-creep) before any install\r\n```\r\n\r\n## Related Tools\r\n\r\n- **clone-farm-detector** — Detects content-level cloning for reputation gaming;\r\n  social-trust-manipulation-detector catches social-level gaming that can occur\r\n  even with original, non-cloned content\r\n- **publisher-identity-verifier** — Verifies publisher identity integrity;\r\n  sockpuppet networks may impersonate multiple independent publishers when they\r\n  are controlled by a single actor\r\n- **trust-velocity-calculator** — Quantifies trust decay from update velocity;\r\n  manufactured trust does not decay the same way as earned trust and creates\r\n  distorted velocity measurements\r\n- **blast-radius-estimator** — Estimates propagation impact if a skill is\r\n  compromised; skills with manufactured trust may have artificially high install\r\n  counts that misrepresent actual blast radius\r\n\r\n## Limitations\r\n\r\nSocial trust manipulation detection depends on access to engagement metadata\r\n(account creation dates, cross-voting patterns, install counts) that many\r\nmarketplaces do not expose through public APIs. Where metadata is limited,\r\nonly velocity analysis and review text assessment are available, which reduces\r\ndetection confidence. Burst voting patterns can result from legitimate causes:\r\ncoordinated community launches, press coverage, or featured placement can all\r\nproduce rapid engagement that resembles manufactured trust. The account cohort\r\nanalysis relies on observable fingerprints and will miss well-resourced\r\nadversaries who age accounts and vary patterns. This tool identifies social\r\ntrust signals that warrant investigation — it does not confirm manipulation,\r\nwhich requires access to platform-level data that only marketplace operators\r\ncan verify.\r\n","readmeExcerpt":"--- name: social-trust-manipulation-detector description: > Helps identify coordinated social trust manipulation in agent marketplaces — catching reputation gaming through sockpuppet networks, coordinated upvoting, and manufactured community signals that make unsafe skills appear trusted. version: 1.0.0 metadata: openclaw: requires: bins: [curl, python3] env: [] emoji: \"🎭\" agent_card: capabilities: [social-trust-man","codeSnippets":[],"executableExamples":[],"parameters":{},"dependencies":[],"permissions":[],"extractedFiles":[],"languages":["typescript"],"docsSourceLabel":"CLAWHUB","editorialOverview":"Helps identify coordinated social trust manipulation in agent marketplaces — catching reputation gaming through sockpuppet networks, coordinated upvoting, and manufactured community signals that make unsafe skills appear trusted. --- name: social-trust-manipulation-detector description: > Helps identify coordinated social trust manipulation in agent marketplaces — catching reputation gaming through sockpuppet networks, coordinated upvoting, and manufactured community signals that make unsafe skills appear trusted. version: 1.0.0 metadata: openclaw: requires: bins: [curl, python3] env: [] emoji: \"🎭\" agent_card: capabilities: [social-trust-man","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":400,"uniquenessScore":61,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-04-15T00:45:39.800Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-04-15T00:45:39.800Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-10T06:14:36.198Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. 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