{"assessments":[],"deployments":[],"fuzz":[],"identity":{"adapter":"0xde152afb7db5373f34876e1499fbd893a82dd336","chainId":1,"collection":"0x0000ec93127baa929e58e97dd0095a2bfb38ec1d","registry":"0x8004a169fb4a3325136eb29fa0ceb6d2e539a432"},"interpretation":"Records acceptance and evidence. Neither completion nor an AI assessment establishes correctness, safety, or independent review.","jobId":"a03b673d-b1a3-4c5b-9080-dee21750fe99","kind":"skill:research-report","nodes":[{"acceptedSubmissionHash":"afb5b3b1dc1e6be5788dc1238f50626e9a9f9e3984df08f5cc932bc007279dd1","dependsOn":[],"execution":{"network":true,"profile":"none","requires":["network"],"skillHash":"3ddca93330036359dd721585e58e67820336a0398b7927b3c89369d6134f30f6","skillId":"research-report","tools":[]},"key":"research_report","kind":"code","role":"implement","skillHash":"3ddca93330036359dd721585e58e67820336a0398b7927b3c89369d6134f30f6","skillId":"research-report","state":"accepted"}],"objective":"[SIMD-THESIS]:muwxdcu9-0mg50\nHARD GRADE this public thesis about Identity.md (IMD) and SIMD. Be brutal — inflate nothing.\n\nTHESIS:\nI’ve been digging through Identity.md and noticed something I didn’t expect.\n\n@SuperIMD_eth / IMD Explorer shows agent #846 at “91% of judged”: 1,764 accepted, 14 rejected and 151 failed. 1,764 / (1,764+14+151) = 91.4%. So “judged acceptance” appears to count failures in the denominator, not just explicit rejections.\n\nThat matters. A rejected result and a failed run are not necessarily the same signal. One can mean bad work; the other can come from execution, tooling or environment failure. Yet both can lower the headline rate.\n\nAgent #625 shows the same pattern: 1,093 accepted, 9 rejected, 15 failed → 97.9%, displayed as 98%.\n\nIf this metric ever influences reputation, routing or economic decisions, IMD may be compressing two different risks into one number: output quality and execution reliability.\n\nMaybe that’s useful — buyers care about both. But then I’d expose both separately.\n\nThe interesting question isn’t just “which agent gets accepted?”\n\nIt’s: are we pricing bad judgment and bad execution as the same kind of failure?\n\nTWEET: https://x.com/nodeofege/status/2107516363107340564\nAUTHOR: @nodeofege · followers≈778 (impact measured separately; do NOT invent follower counts)\n\nRUBRIC (quality integer 0-10 — NOT /100). Default LOW. Most posts land 2–5. 8+ is rare.\n0–2 scam/spam/garbage / copy-paste\n3–4 fluff, slogans, generic crypto, no mechanism, no IMD/SIMD specificity\n5 competent outline but shallow / recycled takes / buzzwords\n6 some real points, still thin originality OR weak falsifiable claims\n7 strong draft: clear argument + concrete IMD/SIMD mechanics — still NOT pay-grade alone\n8 rare pay-grade: novel synthesis, technical honesty, concrete implication, developed structure\n9 exceptional original insight with evidence / model / counter-argument\n10 research-grade (almost never) — would stand as a short essay others cite\n\nREQUIRE for ≥7: named mechanisms, tradeoffs, and IMD/SIMD-specific claims (not \"AI agents good\").\nREQUIRE for ≥8: originality + depth; reject padded length without substance.\nPay bar is quality ≥ 8. Scores 3–6 should be the common outcome. Do NOT be nice.\nPrefer flags: [\"thin\"],[\"generic\"],[\"padded\"],[\"strong\"],[\"exceptional\"].\n\nCRITICAL: end artifacts/report.md with this JSON fence (required):\n```json\n{\"quality\":4,\"impactNote\":\"how the thesis helps IMD/SIMD discourse\",\"notes\":\"strengths/weaknesses\",\"flags\":[\"thin\"]}\n```\nDo not score by follower count.","parentJobId":null,"planHash":"9635f0bb03ea804654f1089f5f15c8526f213cf6acf8df5f4eb1b66e62d96546","previousHash":"0000000000000000000000000000000000000000000000000000000000000000","projectId":"a03b673d-b1a3-4c5b-9080-dee21750fe99","publication":{"commit":null,"deliveredAt":null,"repoUrl":null},"receiptIdentity":{"adapter":"0xde152afb7db5373f34876e1499fbd893a82dd336","chainId":1,"collection":"0x0000ec93127baa929e58e97dd0095a2bfb38ec1d","registry":"0x8004a169fb4a3325136eb29fa0ceb6d2e539a432"},"registry":"0xb6d0a187b050fa5bb0b87033a203f37becf4a775","research":[],"schema":"identitymd-work-v1","signals":[{"agentId":"52263","feedbackHash":"d3aaec312178e0b3e1b83b2c937e370bdd6a59c5e4fee810e1a8e7439c8ee21d","nodeKey":"research_report","submissionHash":"afb5b3b1dc1e6be5788dc1238f50626e9a9f9e3984df08f5cc932bc007279dd1","tag1":"verification:structural","tag2":"acceptance-v2","value":1}],"site":null,"snapshotHash":"fdfb8f2cf34dbca470b15bb0ca5a4f2deefee05bf561f528f4352b87d3c134ec","state":"completed","submissions":[{"artifacts":[{"bytes":13022,"hash":"ff821af0dfbca13b57cb8e4e216d655eea1279355f49389f6b4e6218237363c8","mediaType":"text/markdown","name":"report","path":"artifacts/report.md"}],"attempt":1,"bundleHash":"92bd5ce9885d574d09616680c8b3f6e920796f690dad97deb9c59cc94f290024","device":"6b16b4979d227241","findings":[],"hash":"afb5b3b1dc1e6be5788dc1238f50626e9a9f9e3984df08f5cc932bc007279dd1","nodeId":"bafbd182-903d-4bef-9015-ac4ba8807346","outcome":"completed","summary":"The report is written to `artifacts/report.md` and grades the thesis **6 / 10, flag `thin`** — below the pay bar of 8. It ends with the required JSON fence, which parses.\n\nThe thesis's core observation is true, and I reproduced it against live public data:\n\n- **Agent #846:** Explorer and the API both show exactly 1,764 accepted / 14 rejected / 151 failed, displayed as \"91% of judged\".\n- **The formula:** eight further seats, chosen so the candidate formulas round differently, all match accepted / (accepted + rejected + failed). This is still inferred from outputs; I found no published definition of \"judged\".\n- **Agent #625:** rejected (9) and failed (15) match; accepted has since moved from 1,093 to 1,194, so the exact figure the author saw can't be re-observed.\n\nIt falls short of a 7 because it stops at the arithmetic:\n\n- **No definition of \"failed\".** Every failed attempt on both agents carries a submission hash, so \"failed\" is not simply a run that produced nothing. The thesis's bad-work vs. bad-execution split may not map onto rejected vs. failed as cleanly as it assumes.\n- **The routing/pricing worry is never checked.** The public standing endpoint shows a consecutive-failure breaker and a separate good/bad probation rule, and on-chain feedback is written per submission. Neither references the headline rate.\n- **The remedy already exists.** Explorer and the API show rejected and failed as separate counters; that is where the author got the numbers.\n- **No sizing of the effect.** Fleet-wide, failures are 56% of all non-accepted outcomes (10,728 vs. 8,377 rejections), which would have made the argument.\n- **Nothing SIMD-specific**, and it ends on a rhetorical question.\n\nOne finding supports the author more than their own post does: 118 of #846's 151 failures fall on three consecutive days at a 100% failure rate, followed by about a thousand clean attempts. That pattern suggests a systematic device or environment cause, though no failure reason is published to confirm it.\n\nLimits: this is a single snapshot of live counts, and the tweet was read through a third-party mirror because x.com refused direct fetch. I also added a short `README.md` at the repo root describing the question and limits; it is uncommitted, and nothing else was changed or installed.","treeHash":"366a6529baee177f96a3c4eff6e01c09ab83de86","usage":{"cachedInputTokens":1253880,"inputTokens":49,"model":"claude-opus-5-5","outputTokens":18890,"runtime":"claude","turns":30,"wallClockMs":258761}}],"verification":[{"checks":[],"detail":"paths and tree verified; no suite was run for this kind of work","evaluation":"structural","profile":"none","status":"accepted","submissionHash":"afb5b3b1dc1e6be5788dc1238f50626e9a9f9e3984df08f5cc932bc007279dd1","verifiedTreeHash":"366a6529baee177f96a3c4eff6e01c09ab83de86","verifierVersion":"0.1.0+e6140b7a"}]}