{
  "netuid": 15,
  "slug": "de-val",
  "name": "De-Val",
  "symbol": "\u03bf",
  "description": "AI commerce agents",
  "priceTao": 0.033069752,
  "priceUsd": 8.368337309373446,
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  "change7d": 11.81538387672287,
  "change30d": 82.88359319459994,
  "change90d": 0.0,
  "marketCapUsd": 4513032.144892368,
  "volume24hUsd": 743226.1104271818,
  "rootProp": 0.5466930404271458,
  "liquidityUsd": 1941496.8050943108,
  "alphaStaked": 423346.244890359,
  "activeMiners": 2,
  "activeValidators": 12,
  "emissionPct": 0.005607119506183488,
  "emissionPerDayTao": 1.0,
  "registrationCost": 339.80611881,
  "pruningRank": 64,
  "immunityRemaining": 4890,
  "sentiment": "Greed",
  "githubRepo": "https://github.com/ORO-AI/oro",
  "subnetUrl": "https://oroagents.com",
  "scorecard": {
    "adoption": {
      "label": "weak",
      "score": 11,
      "reasons": [
        {
          "tone": "neutral",
          "label": "Stars",
          "value": "7",
          "weight": null
        },
        {
          "tone": "neutral",
          "label": "Contributors",
          "value": "2",
          "weight": null
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        {
          "tone": "neutral",
          "label": "24h volume",
          "value": "$743,226",
          "weight": null
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        {
          "tone": "neutral",
          "label": "Validators",
          "value": "12",
          "weight": null
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        {
          "tone": "negative",
          "label": "Bus factor",
          "value": "Top contributor: 92%",
          "weight": null
        },
        {
          "tone": "neutral",
          "label": "LLM blend",
          "value": "heuristic=5 \u00d7 0.6 + llm=20 \u00d7 0.4",
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    "shipSpeed": {
      "label": "weak",
      "score": 7,
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          "tone": "neutral",
          "label": "Commits 30d",
          "value": "0",
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        },
        {
          "tone": "neutral",
          "label": "Merged PRs 30d",
          "value": "0",
          "weight": null
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        {
          "tone": "neutral",
          "label": "Releases 12m",
          "value": "0",
          "weight": null
        },
        {
          "tone": "negative",
          "label": "Latest push",
          "value": "2025-05-13T09:52:22Z",
          "weight": null
        },
        {
          "tone": "neutral",
          "label": "Momentum",
          "value": "no history (0/30d vs 0/mo avg)",
          "weight": null
        },
        {
          "tone": "neutral",
          "label": "LLM blend",
          "value": "heuristic=5 \u00d7 0.6 + llm=10 \u00d7 0.4",
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    "updatedAt": "2026-04-29T20:41:08.730417+00:00",
    "confidence": 0.82,
    "usefulness": {
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      "reasons": [
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          "tone": "neutral",
          "label": "Durable keywords",
          "value": "1 matched",
          "weight": null
        },
        {
          "tone": "positive",
          "label": "Commodity risk",
          "value": "0 matched",
          "weight": null
        },
        {
          "tone": "neutral",
          "label": "Subnet traction",
          "value": "1/30",
          "weight": null
        },
        {
          "tone": "neutral",
          "label": "LLM blend",
          "value": "heuristic=41 \u00d7 0.6 + llm=38 \u00d7 0.4",
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    "codeQuality": {
      "label": "weak",
      "score": 26,
      "reasons": [
        {
          "tone": "negative",
          "label": "CI",
          "value": "Missing",
          "weight": null
        },
        {
          "tone": "positive",
          "label": "Tests",
          "value": "1 dir(s), framework config",
          "weight": null
        },
        {
          "tone": "positive",
          "label": "Docs",
          "value": "Basic (600 chars)",
          "weight": null
        },
        {
          "tone": "negative",
          "label": "Dep mgmt",
          "value": "None",
          "weight": null
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        {
          "tone": "negative",
          "label": "PR reviews",
          "value": "0.1 avg, 90% self-merge",
          "weight": null
        },
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          "tone": "neutral",
          "label": "Commit quality",
          "value": "0% conventional",
          "weight": null
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        {
          "tone": "neutral",
          "label": "Security hygiene",
          "value": "No SECURITY.md",
          "weight": null
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          "tone": "neutral",
          "label": "LLM blend",
          "value": "heuristic=26 \u00d7 0.6 + llm=25 \u00d7 0.4",
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  "masterScore": 25.0,
  "masterRating": "D",
  "lastUpdatedAt": "2026-04-29T20:21:48Z",
  "isStale": false,
  "masterScorePrev": 25.0,
  "purpose": {
    "title": "De-Val",
    "source": "llm",
    "confidence": 0.72,
    "shortSummary": "De-Val is a decentralized LLM evaluation subnet with zero development activity in the past 90 days, only 2 active miners, and a 2-person team with a 0.92 top-contributor concentration. Despite an 83% 30-day price surge and $4.5M market cap, the execution signals are critically weak \u2014 no CI, zero recent commits, and a 0.9 self-merge ratio indicate a stalled project."
  },
  "analysis": {
    "risks": [
      "Development is completely stalled: 0 commits in 30d and 90d, 0 merged PRs in 30d, and 0 releases in 12 months \u2014 the project appears abandoned",
      "Extreme bus factor: 2 total contributors with the top contributor at 92% of activity, self-merge ratio of 0.9, and only 2 active miners \u2014 the network has almost no operational depth"
    ],
    "score": 25,
    "summary": "De-Val is a decentralized LLM evaluation subnet with zero development activity in the past 90 days, only 2 active miners, and a 2-person team with a 0.92 top-contributor concentration. Despite an 83% 30-day price surge and $4.5M market cap, the execution signals are critically weak \u2014 no CI, zero recent commits, and a 0.9 self-merge ratio indicate a stalled project.",
    "provider": "cascade:sonnet",
    "expiresAt": "2026-05-29T20:30:31.360683+00:00",
    "strengths": [
      "Decentralized LLM evaluation addresses a genuine infrastructure need in the AI space with some differentiation from pure commodity offerings",
      "MIT license present, tests exist, and docs are included \u2014 foundational repo hygiene signals (hasTests: true, hasLicense: true, hasDocs: true)",
      "24h volume of $743K against a $4.5M market cap shows active trading liquidity relative to size, with 12 active validators providing some network participation"
    ],
    "updatedAt": "2026-04-29T20:30:31.360683+00:00",
    "durability": "weak",
    "recommendation": "Avoid until development resumes with meaningful commit velocity and miner count grows substantially above 2 \u2014 the current signals indicate an abandoned or pre-launch project trading on speculation rather than utility.",
    "dimensionScores": {
      "adoption": 20,
      "shipSpeed": 10,
      "usefulness": 38,
      "codeQuality": 25
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  },
  "repoCoverageStatus": "covered",
  "image": "https://oroagents.com/apple-icon.png?apple-icon.03kgs0ex356h..png",
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      "netuid": 15,
      "repoKind": "primary",
      "provider": "github",
      "owner": "deval-core",
      "name": "De-Val",
      "url": "https://github.com/deval-core/De-Val",
      "source": "registry",
      "isArchived": false,
      "isFork": false
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          "name": "Python",
          "percentage": 99.9
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      "label": "Website",
      "href": "https://oroagents.com"
    },
    {
      "label": "GitHub",
      "href": "https://github.com/ORO-AI/oro"
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      "text": "Congratulations to \"favourite\" (5D4f7J...4by4) winning Race #8 with a score of 49.2%! Over the next day, they'll win $5,500",
      "created_at": "2026-04-21T23:10:56-03:00",
      "likes": 42,
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    {
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      "handle": "oroagents",
      "text": "Introducing: bittensor-auth. \n\nOne of the biggest barriers to Bittensor adoption is difficulty of use.\n\nRead about how we've fixed it (and open sourced the solution):",
      "created_at": "2026-04-21T19:50:49-03:00",
      "likes": 214,
      "retweets": 31,
      "replies": 6,
      "views": 28904,
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    {
      "tweet_id": "2046687841686839750",
      "handle": "oroagents",
      "text": "Congratulations to \"approving\" (5CDar4...jU8J) for winning $5,550 with a score of 58.8% on Race #7!",
      "created_at": "2026-04-21T17:29:41-03:00",
      "likes": 61,
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    {
      "tweet_id": "2046465136991330402",
      "handle": "oroagents",
      "text": "Without @shibshib89 and @dlawee\u2019s support from day 0, we wouldn\u2019t be able to run this subnet. Thank you to the Crucible Labs team for believing in us \u2764\ufe0f\n\nThis is just the beginning.",
      "created_at": "2026-04-21T02:44:44-03:00",
      "likes": 70,
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      "replies": 0,
      "views": 3120,
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    {
      "tweet_id": "2046353838949515630",
      "handle": "oroagents",
      "text": "RT @shardiban: back in the day when the output of the final layer of an encoder-decoder model like bert was fed into the first layer of gpt\u2026",
      "created_at": "2026-04-20T19:22:29-03:00",
      "likes": 87,
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    {
      "tweet_id": "2046288314295373953",
      "handle": "oroagents",
      "text": "Introducing Oro, the biggest agent competition in the world.\n\nPowered by Bittensor, Live Now. https://t.co/IE9MyzHBGM",
      "created_at": "2026-04-20T15:02:06-03:00",
      "likes": 838,
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    {
      "tweet_id": "2046204591016923553",
      "handle": "oroagents",
      "text": "OpenAI is Losing to Open Source. \n\nWe quietly launched on Bittensor 3 weeks ago.\n\nSince then, 45 of our agents have beaten GPT 5.4 at one of the hardest online shopping evals made so far.\n\nThe best agent achieved a 63.0% Success Rate, performing over 15 points better than OpenAI's GPT-5.4.  \n\nWe've achieved this by building the most ambitious software competition in the world.\n\nConventional wisdom says you need scale, billions in compute, proprietary data, and massive teams to build the best state of the art software.\n\nBut we've proven this wrong. What you actually need is competition.\n\nEvery day, armies of developers around the world study failure cases, make critical improvements in logic, and resubmit constantly. Every cooldown, agents are incrementally perfected.   \n\nBittensor is the perfect platform for this.\n\nMiners on the network submit agents. Validators evaluate them against real, difficult tasks. Every evaluation is public and every trajectory is inspectable. You can see exactly where every single agent succeeded and where it failed.\n\nThe top labs have poured hundreds of billions of dollars into their agents, yet ORO has been able to beat them without using any proprietary APIs. How? Every agent is open-source served through @chutes_ai. \n\nThis should seriously bother you if you work at a frontier lab.\n\nWhen you have incentivized developers studying past solutions, working together, and iterating multiple times a day, you get the fastest R&D flywheel in the world.\n\nIn just 21 days, we've already proven that the collective intelligence of Bittensor, combined with a fiercely competitive environment, beats the output of any centralized funded lab. \n\nImagine what we'll do in a year.",
      "created_at": "2026-04-20T09:29:25-03:00",
      "likes": 405,
      "retweets": 81,
      "replies": 28,
      "views": 48090,
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    {
      "tweet_id": "2045199733400949159",
      "handle": "oroagents",
      "text": "How Oro Prevents Cheating",
      "created_at": "2026-04-17T14:56:29-03:00",
      "likes": 21,
      "retweets": 4,
      "replies": 1,
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    {
      "tweet_id": "2044955504896593957",
      "handle": "oroagents",
      "text": "https://t.co/SGlkMzQkdW",
      "created_at": "2026-04-16T22:46:00-03:00",
      "likes": 34,
      "retweets": 2,
      "replies": 2,
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    {
      "tweet_id": "2044208805118898360",
      "handle": "oroagents",
      "text": "We're giving out $5,000 per day to top agents who compete in our software competition!\n\nNo application or requirements. Just deploy, compete, and win. \n\nThe best builders deserve to get paid for building great software. We are officially live!",
      "created_at": "2026-04-14T21:18:53-03:00",
      "likes": 33,
      "retweets": 5,
      "replies": 1,
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    {
      "tweet_id": "2042540544027656678",
      "handle": "oroagents",
      "text": "Thank you, Covenant. https://t.co/ge3cHNvMd2",
      "created_at": "2026-04-10T06:49:48-03:00",
      "likes": 63,
      "retweets": 2,
      "replies": 7,
      "views": 5986,
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    {
      "tweet_id": "2041644353735815619",
      "handle": "oroagents",
      "text": "Who's working on a good set of open benchmarks for agentic commerce? https://t.co/0SXe2aydLD",
      "created_at": "2026-04-07T19:28:40-03:00",
      "likes": 13,
      "retweets": 1,
      "replies": 1,
      "views": 461,
      "is_retweet": false,
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    {
      "tweet_id": "2040961878307053781",
      "handle": "oroagents",
      "text": "We've seen a lot of AI companies demo their agents. \n\nAlmost nobody tests if it actually works.",
      "created_at": "2026-04-05T22:16:45-03:00",
      "likes": 20,
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}