The system prompt is made once per session (start, compaction, model switch), kept in session_meta and resent byte for byte; it holds no date. What changes mid-session -- the date, a mode the person chose, a plan or memory or instruction file they edited, a personality, MCP instructions that arrived later -- is a <session-note> on the next user message, stored with it. The tool list is fixed for the session: plan_submit is always offered and answers unavailable outside plan mode, the wrap-up keeps the tools and runs no call, a withdrawn tool stays listed and answers its refusal; the first request waits up to mcp_wait_ms for MCP servers. Compaction asks for its summary as the next turn of the same conversation. Cached input tokens are parsed (incl. llama.cpp timings), stored per request and shown in /context. Spec: context.md §7/§10, loop.json context.note (+ plan_ended, plan_own, personal, empty, mcp_wait_ms), modes.json plan.refused, compact.md without the transcript heading. Conformance area prefix. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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@@ -23,6 +23,9 @@ import { CONTEXT, hunks, lineCount, memoryResults, presentIds, ResultContext, sh
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import { readBody } from "../src/tool/read.ts"
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import { applyOps, type Op, type Target } from "../src/memory/store.ts"
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import { jobNote, type NoteCase } from "../src/jobs/note.ts"
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import { compactAsk, noteFor, offeredFor, toldAt, unavailable, type Now, type Requirement, type Told } from "../src/session/prefix.ts"
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import { promptText } from "../src/prompt/assemble.ts"
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import { TOOL_SPECS } from "../src/harness.ts"
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type Case = Record<string, unknown>
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@@ -150,6 +153,58 @@ export const AREAS: Record<string, (c: Case) => unknown> = {
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return text
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})
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},
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// The prefix (context.md §10): one session's requests, step by step — which prompt each sends (a
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// new number each time one is made), which tools it offers, and the note on a user message.
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prefix: (c) => {
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const start = c.start as Partial<Now> & { could?: Requirement[]; met?: Requirement[] }
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const could = new Set<Requirement>(start.could ?? [])
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let met = new Set<Requirement>(start.met ?? could)
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const now: Now = { date: start.date!, mode: start.mode ?? "manual", plan: start.plan ?? "", memory: start.memory ?? "", personality: start.personality ?? "", files: start.files ?? {}, mcp: start.mcp ?? {} }
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const modeText = (m: Mode) => fillPrompt(promptText(`modes/${m}.md`), { plan_dir: (c.plan_dir as string | undefined) ?? ".agent/plans" })
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const requires = (t: string) => TOOL_SPECS[t]?.requires as Requirement[] | undefined
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let made: { system: number; tools: string[]; told: Told } | undefined
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let prompts = 0
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let carried: string | undefined
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const make = () => {
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if (made) return made
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made = { system: ++prompts, tools: (c.tools as string[]).filter((t) => offeredFor(requires(t), could)), told: { ...toldAt(now), ...(carried ? { date: carried } : {}) } }
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carried = undefined
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return made
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}
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const fields = ["date", "mode", "plan", "memory", "personality", "files", "mcp"] as const
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return (c.steps as Record<string, any>[]).map((st) => {
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if (st.op === "set") {
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for (const f of fields) if (f in st) (now as unknown as Record<string, unknown>)[f] = structuredClone(st[f])
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if (st.met) met = new Set(st.met)
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// The model's own tool changed it: its result told the model.
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if (st.by === "model" && made) for (const f of fields) if (f in st && f !== "date") (made.told as unknown as Record<string, unknown>)[f] = structuredClone(st[f])
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return null
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}
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if (st.op === "call") {
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const here = new Set(met)
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if (now.mode === "plan") here.add("plan")
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else here.delete("plan")
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return unavailable(st.tool, requires(st.tool), here) ?? null
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}
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if (st.op === "model") {
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carried = made?.told.date
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made = undefined
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return null
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}
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const k = make()
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if (st.op === "user") {
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const { note, told } = noteFor(k.told, now, modeText)
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if (note) k.told = told
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return { system: k.system, tools: k.tools, note: note || null }
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}
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if (st.op === "tool" || st.op === "wrapup") return { system: k.system, tools: k.tools, note: null }
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if (st.op === "compact") {
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made = undefined
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return { system: k.system, tools: k.tools, ask: compactAsk() }
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}
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throw new Error(`prefix: unknown op ${String(st.op)}`)
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})
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},
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library_scope: (c) => resolveBase(c.bases as { id: string; name: string }[], c.base as string | null),
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toolcall_index: (c) => {
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// The deltas as the OpenAI stream carries them: `function.name` and `function.arguments`.
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