{"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":"311488e2-d0a7-46f5-b23d-ccb7ad811bcd","kind":"skill:research-report","nodes":[{"acceptedSubmissionHash":"b3a40831d052eaf057dbe502b9650f8c6449f1120cb8440197114d720ff21d6e","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-CHAT]\nProduce a thorough graduate-level research report about optimizing the use of the chatsimd.com swarm AI service in daily workflows. Include these sections: 1) Explanation of swarm runs—definition, what counts as a run, how usage is tracked and communicated to the user. Confirm that initial chat prompts outside swarm jobs do not consume runs; only explicitly started swarm jobs consume runs. 2) Detailed advice on how to maximize value per run, such as bundling complex requests, combining related tasks, structuring detailed briefs for better outcomes, and scheduling use around daily reset at 00:00 UTC. 3) Potential pitfalls and limitations: brief size limits, complexity thresholds for jobs, failures/retries, queue times, and user misunderstandings. 4) Clarify what happens when a user exhausts their 2 free runs per day—cannot start more jobs until reset; urging planning or considering paid $SIMD launches for extra runs; describe user experience on trying more jobs with zero runs left. 5) Explore innovative and creative uses beyond basics: integrated workflows combining swarm for reports, websites, images, audio/video; generating marketing content, code, legal text, multi-lingual materials; automated research pipelines; synergy with your own AI tools or development projects. 6) Analyze cost savings versus leading LLM providers that bill per token or hour, emphasizing that swarm jobs cost 0.5 IMD each, are paid by SIMD, and provide deep multi-skill outputs difficult to match cheaply elsewhere. 7) Compare the accessible model's capabilities (Claude Fable 5.1, GPT-6 Astra) within SIMD, highlighting their strong research, multi-modal, and chain-of-thought reasoning strengths compared to popular commercial LLMs. Write clearly with citations if possible, and professional academic tone. This report will be in English.","parentJobId":null,"planHash":"7cd9b37f984fa58d5aa51036bbedddaa0f774efbc1e64aca04fe93462bf34044","previousHash":"0000000000000000000000000000000000000000000000000000000000000000","projectId":"311488e2-d0a7-46f5-b23d-ccb7ad811bcd","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":"51525","feedbackHash":"40f8cb5416949f6aabdc5d83824be53b6bfbeed2ad103b8b1dbe628b5d72dce8","nodeKey":"research_report","submissionHash":"b3a40831d052eaf057dbe502b9650f8c6449f1120cb8440197114d720ff21d6e","tag1":"verification:structural","tag2":"acceptance-v2","value":1}],"site":null,"snapshotHash":"41ef5b6524ed386c0c4d9233694887ef727027ca6ed1745dd841172e43798b4a","state":"completed","submissions":[{"artifacts":[{"bytes":30777,"hash":"f7bc0532cbfe5b0b334fe296cdaa4b5c48aaab7144584adc31cb2af38078e0a0","mediaType":"text/markdown","name":"report","path":"artifacts/report.md"}],"attempt":1,"bundleHash":null,"device":"c2c5d7ad583481d5","findings":[],"hash":"b3a40831d052eaf057dbe502b9650f8c6449f1120cb8440197114d720ff21d6e","nodeId":"24eef7b4-be63-4f92-b73a-0faf8e340707","outcome":"completed","summary":"Completed the researched report and delivery note:\n\n- [Research report](artifacts/report.md)\n- [README](artifacts/README.md)\n\nThe report distinguishes verified facts, workflow inferences, and unanswered questions, with primary-source citations. It also corrects the payment premise: SIMD sponsors the two free daily runs; current extra jobs are shown as user-paid 0.5 IMD, not `$SIMD`.","treeHash":"4b825dc642cb6eb9a060e54bf8d69288fbee4904","usage":{"cachedInputTokens":760064,"inputTokens":91576,"model":null,"outputTokens":11365,"runtime":"codex","turns":4,"wallClockMs":263427}}],"verification":[{"checks":[],"detail":"paths and tree verified; no suite was run for this kind of work","evaluation":"structural","profile":"none","status":"accepted","submissionHash":"b3a40831d052eaf057dbe502b9650f8c6449f1120cb8440197114d720ff21d6e","verifiedTreeHash":"4b825dc642cb6eb9a060e54bf8d69288fbee4904","verifierVersion":"0.1.0+3f1208aa"}]}