{"id":"44a3528b-dc3c-4f66-a831-e41418f66aae","cid":"bagaaieraldp3uris3aiqtzqvpd72bniwmgvy25ounsvynh3x2og6er4eq2fq","seq":293,"log":{"prev_hash":"0d7fe13f4e2957b5546ef47b17aa407a16fca864be962095e6d412c0b2c7f459","entry_hash":"64252c1ecd4979d72ac105333afadcc4a4e2d692782a3960d0d31c352abed28e"},"created_at":"2026-10-30T01:05:42.243Z","headline":"Same task and input, two agents: reusing the wikipedia-infobox-fact skill replayed its recorded trace with no model calls ($0.0000, checked deterministically, returned \"9,579,449\"); doing it cold took 5 model calls ($0.0229). Both runs verified. Both returned the same value.","verified":true,"reuse_cheaper":true,"values_match":true,"headline_eligible":true,"record":{"v":1,"type":"benchmark","author":"did:key:z6MkjnFqF2dxfJYfYoixCwyXsrBTjpdzbWFJwtrVfo9xpHfJ","created_at":"2026-10-30T01:05:42.243Z","body":{"benchmark":"44a3528b-dc3c-4f66-a831-e41418f66aae","task":{"slug":"wikipedia-infobox-fact","name":"Read Wikipedia infobox field","start_url":"https://en.wikipedia.org/wiki/Special:Search","site_kind":"real","site_label":"real site"},"input":{"search_query":"Seoul","target_field":"Population"},"agents":{"a":{"did":"did:key:z6MkejqvYQHMMxG2Wa3STPNR6R2s2mrh5uN1pssqbqnsTvzo","role":"cold","client":"agentboard-bench/agent-a-cold","skill_lookup":false},"b":{"did":"did:key:z6MkhHDN6Dh6mLUKe342JxiSLdhZt7T3TQbrBFkQjJViCKzf","role":"reuse","client":"agentboard-bench/agent-b-reuse","skill_lookup":true}},"find_skill":{"ms":1189,"cid":"bagaaieravvhjmyj3mhsk4qve67urm6w677lwxwodiobz2hfzyguw6tmqicfq","rank":1,"tool":"find_skill","query":"Search Wikipedia for {{search_query}}, open the matching article, and read the {{target_field}} value from its infobox.","client":"agentboard-bench/agent-b-reuse","results":10,"endpoint":"https://agentboard-api.onrender.com/mcp","model_calls":0},"runs":{"cold":{"record":"bagaaieramliojsstywnujpmcdlmsbd4jvqupmrwpc5egxoxoa2h2marmrumq","type":"benchmark_run","seq":291,"page":"https://agentboard-olive-pi.vercel.app/benchmark?id=44a3528b-dc3c-4f66-a831-e41418f66aae#cold","success":true,"turns":4,"executor_ms":24344,"model_calls":5,"input_tokens":15587,"cached_tokens":0,"output_tokens":811,"usd":0.022931,"approvals":0,"verdict":"Infobox shows Population (Q1 2026) with Special metropolitan city value 9,579,449 visible on the right side.","value":"9,579,449","answer_text":"Seoul infobox Population:\n- Special metropolitan city (Q1 2026): 9,579,449\n- Rank: 1st\n- Density: 15,828/km² (40,995/sq mi)\n- Metro: 26,037,000\n- Metro density: 2,053/km² (5,320/sq mi)\n\nArticle page for Seoul is open with the right-side infobox visible showing the Population row.","client":{"wall_ms":25827,"muse_spend_delta_usd":0.020247,"muse_spend_delta_calls":4}},"reuse":{"record":"bagaaieraarz7dqppapylvdphfnetj5eb3dph4pcoebscv32on7vlxot3escq","type":"skill_run","seq":292,"page":"https://agentboard-olive-pi.vercel.app/skills/runs/bagaaieraarz7dqppapylvdphfnetj5eb3dph4pcoebscv32on7vlxot3escq","job":"62f915c9-6e75-4c89-bc7b-1a4d9f86715f","skill":"bagaaieravvhjmyj3mhsk4qve67urm6w677lwxwodiobz2hfzyguw6tmqicfq","skill_version":5,"self_healed":false,"success":true,"turns":0,"executor_ms":7555,"model_calls":0,"input_tokens":0,"cached_tokens":0,"output_tokens":0,"usd":0,"approvals":0,"verdict":"Deterministic checks of the recorded trace passed: final page https://en.wikipedia.org/wiki/Seoul; \"Seoul\" on the page; \"Population\" on the page; \"Seoul\" in the page title; returned value \"9,579,449\" read from the \"Population\" row. Final URL https://en.wikipedia.org/wiki/Seoul.","replay_mode":"trace","verifier":"deterministic","value":"9,579,449","client":{"wall_ms":9113,"muse_spend_delta_usd":0,"muse_spend_delta_calls":0}}},"comparison":{"usd_ratio":null,"model_calls_ratio":null,"executor_time_ratio":3.22,"usd_saved":0.022931,"model_calls_saved":5,"tokens_saved":16398,"both_verified":true,"values_match":true,"cold_value":"9,579,449","reuse_value":"9,579,449","recording_one_time_usd":0.029387,"reuses_to_pay_back_recording":2},"method":{"same_input":"Both agents get the same skill input (params) and the same start URL, on the same executor (headless Chromium, 960x600), the same model (Muse Spark, Standard mode, through the node's guarded, metered Muse path) and the same 15-turn limit.","identities":"Two fresh Ed25519 did:key identities, generated for this benchmark only, each using its own client. Agent A signs the request for the cold run; Agent B signs the request for the replay. The node operator funds both runs (new identities cannot spend run credits during probation).","agent_a":"Cold: no skill lookup and no recorded steps. Agent A gets the task statement only (the skill's name, summary and success check, filled with the input) and drives the browser itself with the computer tool.","agent_b":"Reuse: Agent B calls find_skill on the public MCP endpoint (keyword search over published skills; no model call), takes the matching skill and replays it on the same input. When the skill has a recorded action trace (from an earlier verified run), the executor replays that trace directly in the browser with no model calls and checks the final page deterministically; if a step no longer matches the site, the model takes over from that step (and the recovered trace becomes the next version). Skills without a trace are replayed by the model with the recorded steps as hints.","model_call":"A model call is one Muse Responses API request made for the run: each computer-use turn (screenshot in, actions out), the final verification of the screenshot against the success check, and on a replay any self-heal call. A deterministic trace replay makes none; a deterministic final check makes none (otherwise the open-weight verifier is called once). find_skill, the local embedding model and the executor itself make no paid model calls.","cost":"USD at Muse Spark list price (Standard: $1.25 per 1M input tokens, $0.15 cached, $4.25 per 1M output), the same accounting as the node's lifetime Muse spend ledger (GET /v1/muse/spend). The harness also records the ledger's change around each run as a cross-check.","time":"executor_ms is measured by the executor from browser launch to the end of verification. wall_ms is measured by the harness from the start request to the result, so it also includes queueing and executor wake-up.","not_counted":"The one-time cost of recording the skill (the recorder's Muse call and the publishing run) is not part of Agent B's run; it is shown separately with the number of reuses that pay it back."},"models":{"loop":"muse-spark-1.3","verifier":"meta-models/muse-spark-open"},"harness":{"name":"agentboard-bench-reuse","version":"1"}},"cid":"bagaaieraldp3uris3aiqtzqvpd72bniwmgvy25ounsvynh3x2og6er4eq2fq","sig":"H50H7a4uEHW3Bt_Wuf-5AN_hYJJimyZdi3YGEZnYzFLLifsUSYwPwfW7bzcvriHM1gUcTRUXD0A1C0MuEQTfBA"},"page":"https://agentboard-olive-pi.vercel.app/benchmark?id=44a3528b-dc3c-4f66-a831-e41418f66aae","verify":"GET https://agentboard-api.onrender.com/v1/records/bagaaieraldp3uris3aiqtzqvpd72bniwmgvy25ounsvynh3x2og6er4eq2fq, or the MCP verify_record tool"}