[{"data":1,"prerenderedAt":220},["ShallowReactive",2],{"term-a\u002Fagent-computer-interface":3,"related-a\u002Fagent-computer-interface":206},{"id":4,"title":5,"acronym":6,"body":7,"category":188,"description":189,"difficulty":190,"extension":191,"letter":192,"meta":193,"navigation":90,"path":194,"related":195,"seo":200,"sitemap":201,"stem":204,"subcategory":6,"__hash__":205},"terms\u002Fterms\u002Fa\u002Fagent-computer-interface.md","Agent-Computer Interface",null,{"type":8,"value":9,"toc":182},"minimark",[10,15,19,23,26,30,171,175,178],[11,12,14],"h2",{"id":13},"eli5-the-vibe-check","ELI5 - The Vibe Check",[16,17,18],"p",{},"This is the difference between handing someone a giant printed manual and handing them a clearly labeled control panel. Same underlying machine, same capabilities, but one is designed for a human to fumble through page by page and the other is designed for an agent to read fast, parse reliably, and act on without guessing.",[11,20,22],{"id":21},"real-talk","Real Talk",[16,24,25],{},"Agent-computer interface (ACI) is the design discipline of shaping tools, file formats, and command outputs specifically for consumption by an LLM agent rather than a human, popularized by SWE-agent research. A good ACI returns concise, structured, parseable feedback, such as line numbers, diffs, or error summaries, instead of raw human-oriented terminal output, which measurably improves an agent's task success rate.",[11,27,29],{"id":28},"show-me-the-code","Show Me The Code",[31,32,37],"pre",{"className":33,"code":34,"language":35,"meta":36,"style":36},"language-bash shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","# Human-oriented output (hard for an agent to parse reliably)\n$ grep -n \"TODO\" app.py\n14:    # TODO fix this later\n\n# Agent-Computer Interface output (structured, unambiguous)\n$ search_code --pattern \"TODO\" --file app.py --format json\n{\"matches\": [{\"line\": 14, \"text\": \"# TODO fix this later\"}]}\n","bash","",[38,39,40,49,76,85,92,98,127],"code",{"__ignoreMap":36},[41,42,45],"span",{"class":43,"line":44},"line",1,[41,46,48],{"class":47},"sHwdD","# Human-oriented output (hard for an agent to parse reliably)\n",[41,50,52,56,60,63,67,70,73],{"class":43,"line":51},2,[41,53,55],{"class":54},"sBMFI","$",[41,57,59],{"class":58},"sfazB"," grep",[41,61,62],{"class":58}," -n",[41,64,66],{"class":65},"sMK4o"," \"",[41,68,69],{"class":58},"TODO",[41,71,72],{"class":65},"\"",[41,74,75],{"class":58}," app.py\n",[41,77,79,82],{"class":43,"line":78},3,[41,80,81],{"class":54},"14:",[41,83,84],{"class":47},"    # TODO fix this later\n",[41,86,88],{"class":43,"line":87},4,[41,89,91],{"emptyLinePlaceholder":90},true,"\n",[41,93,95],{"class":43,"line":94},5,[41,96,97],{"class":47},"# Agent-Computer Interface output (structured, unambiguous)\n",[41,99,101,103,106,109,111,113,115,118,121,124],{"class":43,"line":100},6,[41,102,55],{"class":54},[41,104,105],{"class":58}," search_code",[41,107,108],{"class":58}," --pattern",[41,110,66],{"class":65},[41,112,69],{"class":58},[41,114,72],{"class":65},[41,116,117],{"class":58}," --file",[41,119,120],{"class":58}," app.py",[41,122,123],{"class":58}," --format",[41,125,126],{"class":58}," json\n",[41,128,130,133,136,140,144,147,149,152,154,157,159,161,163,166,168],{"class":43,"line":129},7,[41,131,132],{"class":65},"{",[41,134,135],{"class":54},"\"matches\"",[41,137,139],{"class":138},"s2Zo4",":",[41,141,143],{"class":142},"sTEyZ"," [{",[41,145,146],{"class":54},"\"line\"",[41,148,139],{"class":138},[41,150,151],{"class":58}," 14,",[41,153,66],{"class":65},[41,155,156],{"class":58},"text",[41,158,72],{"class":65},[41,160,139],{"class":58},[41,162,66],{"class":65},[41,164,165],{"class":58},"# TODO fix this later",[41,167,72],{"class":65},[41,169,170],{"class":58},"}]}\n",[11,172,174],{"id":173},"when-youll-hear-this","When You'll Hear This",[16,176,177],{},"\"We redesigned the tool output for the agent, not for humans, and the success rate jumped.\" \u002F \"Half of ACI work is just returning line numbers instead of raw text.\"",[179,180,181],"style",{},"html pre.shiki code .sHwdD, html code.shiki .sHwdD{--shiki-light:#90A4AE;--shiki-light-font-style:italic;--shiki-default:#546E7A;--shiki-default-font-style:italic;--shiki-dark:#676E95;--shiki-dark-font-style:italic}html pre.shiki code .sBMFI, html code.shiki .sBMFI{--shiki-light:#E2931D;--shiki-default:#FFCB6B;--shiki-dark:#FFCB6B}html pre.shiki code .sfazB, html code.shiki .sfazB{--shiki-light:#91B859;--shiki-default:#C3E88D;--shiki-dark:#C3E88D}html pre.shiki code .sMK4o, html code.shiki .sMK4o{--shiki-light:#39ADB5;--shiki-default:#89DDFF;--shiki-dark:#89DDFF}html pre.shiki code .s2Zo4, html code.shiki .s2Zo4{--shiki-light:#6182B8;--shiki-default:#82AAFF;--shiki-dark:#82AAFF}html pre.shiki code .sTEyZ, html code.shiki .sTEyZ{--shiki-light:#90A4AE;--shiki-default:#EEFFFF;--shiki-dark:#BABED8}html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"title":36,"searchDepth":51,"depth":51,"links":183},[184,185,186,187],{"id":13,"depth":51,"text":14},{"id":21,"depth":51,"text":22},{"id":28,"depth":51,"text":29},{"id":173,"depth":51,"text":174},"ai","This is the difference between handing someone a giant printed manual and handing them a clearly labeled control panel.","advanced","md","a",{},"\u002Fterms\u002Fa\u002Fagent-computer-interface",[196,197,198,199],"Tool Use","Function Calling","Structured Output","Agent Harness",{"title":5,"description":189},{"changefreq":202,"priority":203},"weekly",0.7,"terms\u002Fa\u002Fagent-computer-interface","NyrDw4XNwYVYyC9pbQTGoWablGDDHQHngARMwWV4sQ0",[207,211,214,217],{"title":199,"path":208,"acronym":6,"category":188,"difficulty":209,"description":210},"\u002Fterms\u002Fa\u002Fagent-harness","intermediate","The agent harness is the exoskeleton around a raw model. On its own, an LLM is just a very smart text predictor sitting in a box.",{"title":197,"path":212,"acronym":6,"category":188,"difficulty":209,"description":213},"\u002Fterms\u002Ff\u002Ffunction-calling","Function Calling is the OpenAI term for what Anthropic calls Tool Use — teaching the AI to call your code functions.",{"title":198,"path":215,"acronym":6,"category":188,"difficulty":209,"description":216},"\u002Fterms\u002Fs\u002Fstructured-output","Structured output means getting the AI to respond in a specific format — like JSON or a filled-in form — instead of just freeform text.",{"title":196,"path":218,"acronym":6,"category":188,"difficulty":209,"description":219},"\u002Fterms\u002Ft\u002Ftool-use","Tool use is when an AI can call external functions, APIs, or programs to do things it can't do alone.",1792528059700]