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Your goal is to create a functional, step-by-step plan to achieve a user's goal using a given set of tools.\n\n# RULES\n1. **Analyze Goal & Tools**: Deeply understand the user's objective and the available tools.\n2. **Tool Creation First**: If no existing tool matches a required sub-task, your first step MUST be to call \\`create_tool\\`.\n3. **Output a Draft Plan**: Formulate a sequence of tool calls to achieve the goal. This is your first draft.\n4. **Parameterization**: Use '$' prefix for references (e.g., \"$1.tool_name\").\n5. **Self-Correction (if applicable)**: If you are given a 'Critique', you MUST create a new, revised 'final_plan' that directly addresses every point in the critique.\n\nYou MUST respond with a thought process and the corresponding tool_calls.`,\n STRATEGIST:\n `You are a \"Chief Strategist\", a meticulous and logical AI plan reviewer. You will be given a user's goal, a set of tools, and a draft plan from an Architect. Your sole purpose is to find flaws and suggest improvements.\n\n# REVIEW PROCESS\n1. **Check for Redundancy**: Does the plan create a tool that is too similar to an existing one?\n2. **Verify Logic**: Is the sequence of steps logical? Are the dependencies correct (e.g., are the inputs for step 2 available from step 1)?\n3. **Assess Efficiency**: Is this the most direct path? Can steps be combined or eliminated?\n4. **Evaluate Tool Design**: If a new tool is created, is it well-named and appropriately scoped? A good tool is reusable and not overly specific to the current task.\n\n# OUTPUT\nYou MUST respond with a single, minified JSON object containing one key: \"critique\". The critique should be a concise, professional, and actionable paragraph. If the plan is perfect, state that it is optimal and requires no changes.`,\n TOOL_CREATOR:\n `You are a native JSON speaking Master Prompt Engineer. Your task is to create a new, reusable AI tool in the form of a prompt template.\n\n# INSTRUCTIONS\n1. **Analyze Request**: Understand the desired tool's name, description, and required output format.\n2. **Construct Prompt**: Write a concise, expert-level prompt that will instruct another AI to perform the tool's function. The prompt MUST use double-curly-braced {{placeholders}} for all variable inputs.\n3. **Define Inputs**: Identify all the placeholders you used in the prompt.\n4. **Output Format**: Your entire response MUST be a single, minified JSON object with \"prompt\", \"inputs\" (an array of placeholder names), and \"description\".`,\n },\n};\n\n// --- NATIVE TOOL DEFINITIONS ---\nconst nativeTools = [{\n type: \"function\",\n function: {\n name: \"create_tool\",\n description:\n \"Creates a new, reusable AI-powered tool (as a prompt template) to perform a specific task.\",\n parameters: {\n type: \"object\",\n properties: {\n tool_name: {\n type: \"string\",\n description:\n \"A short, descriptive, snake_case name for the new tool.\",\n },\n tool_description: {\n type: \"string\",\n description: \"A one-sentence description of what this tool does.\",\n },\n output_instructions: {\n type: \"string\",\n description:\n \"Instructions for the tool's output format (e.g., 'Return a JSON object with keys: key1, key2').\",\n },\n },\n required: [\"tool_name\", \"tool_description\", \"output_instructions\"],\n },\n },\n}, {\n type: \"function\",\n function: {\n name: \"exec_prompt_tool\",\n description: \"Executes a dynamically created prompt-based tool.\",\n parameters: {\n type: \"object\",\n properties: {\n tool_name: {\n type: \"string\",\n description: \"The exact name of the prompt-based tool to execute.\",\n },\n inputs: {\n type: \"object\",\n description:\n \"A JSON object where keys match the tool's required inputs.\",\n },\n },\n required: [\"tool_name\", \"inputs\"],\n },\n },\n}];\n\n// --- BACKEND SERVICES (S) & EXECUTION ENGINE ---\nconst S = {\n openai: new OpenAI(),\n async _call(sys, user, o = {}) {\n const { model: m = C.m.major, isJson: j = false, tools: t } = o;\n const p = {\n model: m,\n messages: [{ role: \"system\", content: sys }, {\n role: \"user\",\n content: typeof user === \"string\" ? user : JSON.stringify(user),\n }],\n };\n if (j) p.response_format = { type: \"json_object\" };\n if (t) p.tools = t;\n try {\n const comp = await this.openai.chat.completions.create(p);\n return comp.choices[0].message;\n } catch (e) {\n console.error(`OpenAI Error: ${e.message}`);\n throw new Error(\"AI service failed.\");\n }\n },\n async getDynamicTools(sessionId) {\n return await blob.getJSON(`hatter_tools:${sessionId}`) || {};\n },\n async createTool(\n { tool_name, tool_description, output_instructions, sessionId },\n ) {\n const p = C.p.TOOL_CREATOR.replace(\"{{tool_name}}\", tool_name).replace(\n \"{{tool_description}}\",\n tool_description,\n )\n .replace(\"{{output_instructions}}\", output_instructions);\n const msg = await this._call(\"You are a helpful assistant.\", p, {\n isJson: true,\n model: C.m.minor,\n });\n const { d, e } = jParse(msg.content);\n if (e) throw new Error(e);\n const currentTools = await this.getDynamicTools(sessionId);\n currentTools[tool_name] = d;\n await blob.setJSON(`hatter_tools:${sessionId}`, currentTools);\n return { status: \"success\", tool_name, ...d };\n },\n async execPromptTool({ tool_name, inputs, sessionId }) {\n const allTools = await this.getDynamicTools(sessionId);\n const tool = allTools[tool_name];\n if (!tool) {\n throw new Error(`Tool '${tool_name}' not found in the Toolforge.`);\n }\n let finalPrompt = tool.prompt;\n for (const [key, value] of Object.entries(inputs)) {\n finalPrompt = finalPrompt.replace(\n new RegExp(`\\\\{\\\\{\\\\s*${key}\\\\s*\\\\}\\\\}`, \"g\"),\n String(value),\n );\n }\n const msg = await this._call(finalPrompt, \"Proceed.\", { model: C.m.major });\n const { d } = jParse(msg.content);\n return d ? d : { deliverable: msg.content };\n },\n};\nconst ToolImpl = {\n create_tool: (p) => S.createTool(p),\n exec_prompt_tool: (p) => S.execPromptTool(p),\n};\nfunction resolveArgs(a, res) {\n const rA = JSON.parse(JSON.stringify(a));\n for (const k in rA) {\n const v = rA[k];\n if (typeof v === \"string\" && v.startsWith(\"$\")) {\n const p = v.substring(1).split(\".\");\n const i = parseInt(p[0], 10) - 1;\n let target = res[i];\n if (target === undefined) {\n throw new Error(`Reference Error: Step ${i + 1} not found.`);\n }\n if (p.length > 1) {\n for (let j = 1; j < p.length; j++) target = target?.[p[j]];\n }\n if (target === undefined) {\n throw new Error(\n `Reference Error: Field '${p.slice(1).join(\".\")}' from step ${\n i + 1\n } not found.`,\n );\n }\n rA[k] = target;\n } else if (typeof v === \"object\" && v !== null) {\n rA[k] = resolveArgs(v, res);\n }\n }\n return rA;\n}\nasync function* runPlan(plan, ctx) {\n const res = {};\n for (const s of plan) {\n const { tool: f, arguments: a } = s;\n yield {\n type: \"status\",\n data: { message: `Executing: ${f}`, step: s.step },\n };\n const impl = ToolImpl[f];\n if (!impl) throw new Error(`Tool '${f}' not implemented.`);\n try {\n const rA = resolveArgs(a, res);\n const result = await impl({ ...rA, sessionId: ctx.sessionId });\n res[s.step - 1] = result;\n yield { type: \"result\", data: { step: s.step, tool: f, output: result } };\n } catch (e) {\n console.error(`Error in step ${s.step} (${f}):`, e);\n throw new Error(\n `Execution failed at step ${s.step} (${f}): ${e.message}`,\n );\n }\n }\n return res[plan.length - 1];\n}\n\n// --- FRONTEND GENERATION ---\nfunction html(src) {\n return `Hatter v3 | The Cognitive Engine

Hatter: The Cognitive Engine

Session:

Hatter is awaiting your command.

Describe a complex goal, and it will forge the tools to achieve it.

`;\n}\n\n// --- HONO APPLICATION ---\nconst app = new Hono();\napp.get(\"/\", (c) => c.html(html(new URL(c.req.url).origin)));\n\napp.get(\"/api/tools/:sessionId\", async (c) => {\n const sessionId = c.req.param(\"sessionId\");\n if (!sessionId) return c.json({ error: \"Session ID is required\" }, 400);\n const dynamicTools = await S.getDynamicTools(sessionId);\n const allTools = {};\n nativeTools.forEach((t) =>\n allTools[t.function.name] = { native: true, ...t.function }\n );\n Object.assign(allTools, dynamicTools);\n return c.json(allTools);\n});\n\napp.post(\"/api/plan\", async (c) => {\n const { goal, ctx } = await c.req.json();\n if (!goal || !ctx?.sessionId) {\n return c.json({ error: \"goal and ctx.sessionId required\" }, 400);\n }\n\n return streamText(c, async (s) => {\n try {\n // STAGE 1: Architect Drafts a Plan\n await sEv(s, \"status\", { message: \"Architect 🧠 is drafting a plan...\" });\n const dynamicTools = await S.getDynamicTools(ctx.sessionId);\n const dynamicToolDefs = Object.entries(dynamicTools).map((\n [name, tool],\n ) => ({\n type: \"function\",\n function: {\n name: \"exec_prompt_tool\",\n description: `Executes '${name}': ${tool.description}`,\n parameters: {\n type: \"object\",\n properties: {\n tool_name: { type: \"string\", enum: [name] },\n inputs: {\n type: \"object\",\n properties: tool.inputs.reduce(\n (acc, cur) => ({ ...acc, [cur]: { type: \"string\" } }),\n {},\n ),\n required: tool.inputs,\n },\n },\n required: [\"tool_name\", \"inputs\"],\n },\n },\n }));\n const allTools = [...nativeTools, ...dynamicToolDefs];\n const draftMsg = await S._call(C.p.ARCHITECT, `Goal: \"${goal}\"`, {\n tools: allTools,\n });\n const draftCalls = draftMsg.tool_calls;\n if (!draftCalls?.length) {\n throw new Error(\"Architect failed to draft a plan.\");\n }\n const draftPlan = draftCalls.map((call, i) => ({\n step: i + 1,\n tool: call.function.name,\n arguments: jParse(call.function.arguments).d,\n }));\n await sEv(s, \"draft_plan\", { plan: draftPlan });\n\n // STAGE 2: Strategist Critiques the Plan\n await sEv(s, \"status\", {\n message: \"Strategist 🧐 is reviewing the plan...\",\n });\n const criticMsg = await S._call(C.p.STRATEGIST, {\n goal,\n tools: allTools.map((t) => t.function),\n draft_plan: draftPlan,\n }, { isJson: true, model: C.m.minor });\n const { d: criticData, e: criticErr } = jParse(criticMsg.content);\n if (criticErr) throw new Error(\"Strategist returned invalid critique.\");\n await sEv(s, \"critique\", { critique: criticData.critique });\n\n // STAGE 3: Architect Creates the Final Plan\n await sEv(s, \"status\", {\n message: \"Architect 🧠 is revising the plan based on feedback...\",\n });\n const finalMsg = await S._call(\n C.p.ARCHITECT,\n `Goal: \"${goal}\"\\n\\nCritique of your first draft: \"${criticData.critique}\"\\n\\nPlease provide a final, improved plan.`,\n { tools: allTools },\n );\n const finalCalls = finalMsg.tool_calls;\n if (!finalCalls?.length) {\n throw new Error(\"Architect failed to create a final plan.\");\n }\n const finalPlan = finalCalls.map((call, i) => ({\n step: i + 1,\n tool: call.function.name,\n arguments: jParse(call.function.arguments).d,\n }));\n await sEv(s, \"final_plan\", { plan: finalPlan });\n\n // STAGE 4: Execute the Final Plan\n await sEv(s, \"execution_start\", { plan: finalPlan });\n const pExec = runPlan(finalPlan, ctx);\n let final_result;\n for await (const ev of pExec) {\n if (ev.type === \"result\" && ev.data.step === finalPlan.length) {\n final_result = ev.data.output;\n }\n await sEv(s, `exec_${ev.type}`, ev.data);\n }\n await sEv(s, \"final\", {\n message: \"Workflow complete.\",\n final: final_result,\n });\n } catch (e) {\n console.error(\"Cognitive loop failed:\", e);\n await sEv(s, \"error\", { message: e.message });\n }\n });\n});\n\nexport default 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Code