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centdix 3f5f211a22 add final context size metric to ai_evals harness (#9660)
Record finalContextTokens per attempt: the input-token total of the last
model request (input + cache-creation + cache-read), i.e. how full the
context window ended up. Complements the cumulative tokenUsage.prompt,
which conflates context size with loop-iteration count.

Captured generically in the shared frontend runEval via the chat loop's
lastIterationUsage, so it covers all frontend modes (global/flow/script/
app), plus CLI mode via the last assistant turn's usage. Aggregated as
average and max over passed attempts and printed in the run summary.

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-18 23:21:28 +02:00

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import { query, type Options } from "@anthropic-ai/claude-agent-sdk";
import { chmod, mkdir, readFile, writeFile } from "node:fs/promises";
import { delimiter, join } from "path";
import { fileURLToPath } from "url";
import { getCliEvalModel, resolveEvalModel, type CliEvalModelConfig } from "../../core/models";
import type {
BenchmarkTokenUsage,
CliToolInvocation,
CliTrace,
CliWmillInvocation,
} from "../../core/types";
export type ToolInvocation = CliToolInvocation;
export interface PromptRunResult {
output: string;
durationMs: number;
tokenUsage: BenchmarkTokenUsage | null;
// Input tokens on the last assistant turn. The SDK `result` message reports
// usage cumulatively, so the final context size comes from per-turn usage.
finalContextTokens: number | null;
trace: CliTrace;
}
interface AnthropicUsageLike {
input_tokens?: number | null;
output_tokens?: number | null;
cache_creation_input_tokens?: number | null;
cache_read_input_tokens?: number | null;
}
interface AnthropicModelUsageLike {
inputTokens?: number | null;
outputTokens?: number | null;
cacheCreationInputTokens?: number | null;
cacheReadInputTokens?: number | null;
}
interface CliResultMessageLike {
type?: string;
usage?: AnthropicUsageLike | null;
modelUsage?: Record<string, AnthropicModelUsageLike> | null;
}
const REPO_ROOT = fileURLToPath(new URL("../../../", import.meta.url));
export const DEFAULT_CLI_EVAL_MODEL: CliEvalModelConfig = getCliEvalModel(resolveEvalModel("cli"));
const WMILL_STUB_DIR_NAME = ".wmill-benchmark-bin";
const WMILL_LOG_FILE_NAME = ".wmill-benchmark-wmill-invocations.log";
const WMILL_LOG_MARKER = "__WMILL_BENCHMARK__";
const NEGATED_COMMAND_PREFIX = /(?:^|\b)(?:do not|don't|dont|never|instead of)\s+(?:run|use)?\s*$/i;
const COMMAND_STOP_WORDS = new Set([
"and",
"before",
"after",
"then",
"instead",
"otherwise",
"because",
"so",
"if",
"when",
"while",
"once",
]);
const COMMAND_STOP_TOKENS = new Set(["-", "", "—", "|"]);
export function getGeneratedSkillsSource(): string {
return join(REPO_ROOT, "system_prompts", "auto-generated", "skills");
}
export function anthropicUsageToBenchmarkTokenUsage(
usage: AnthropicUsageLike | null | undefined
): BenchmarkTokenUsage | null {
if (!usage) {
return null;
}
const prompt =
(usage.input_tokens ?? 0) +
(usage.cache_creation_input_tokens ?? 0) +
(usage.cache_read_input_tokens ?? 0);
const completion = usage.output_tokens ?? 0;
return {
prompt,
completion,
total: prompt + completion,
};
}
export function extractCliResultTokenUsage(message: unknown): BenchmarkTokenUsage | null {
if (!message || typeof message !== "object") {
return null;
}
const resultMessage = message as CliResultMessageLike;
if (resultMessage.type !== "result") {
return null;
}
const usage = anthropicUsageToBenchmarkTokenUsage(resultMessage.usage);
if (usage) {
return usage;
}
if (!resultMessage.modelUsage || typeof resultMessage.modelUsage !== "object") {
return null;
}
let prompt = 0;
let completion = 0;
let sawModelUsage = false;
for (const modelUsage of Object.values(resultMessage.modelUsage)) {
if (!modelUsage || typeof modelUsage !== "object") {
continue;
}
prompt +=
(modelUsage.inputTokens ?? 0) +
(modelUsage.cacheCreationInputTokens ?? 0) +
(modelUsage.cacheReadInputTokens ?? 0);
completion += modelUsage.outputTokens ?? 0;
sawModelUsage = true;
}
if (!sawModelUsage) {
return null;
}
return {
prompt,
completion,
total: prompt + completion,
};
}
export async function runPromptAndCapture(
prompt: string,
cwd: string,
maxTurns: number = 3,
modelConfig: CliEvalModelConfig = DEFAULT_CLI_EVAL_MODEL
): Promise<PromptRunResult> {
const toolsUsed: ToolInvocation[] = [];
const skillsInvoked: string[] = [];
const bashCommands: string[] = [];
let output = "";
let assistantMessageCount = 0;
let tokenUsage: BenchmarkTokenUsage | null = null;
let finalContextTokens: number | null = null;
const startedAt = Date.now();
const stubBinDir = join(cwd, WMILL_STUB_DIR_NAME);
const wmillLogPath = join(cwd, WMILL_LOG_FILE_NAME);
const options: Options = {
cwd,
model: modelConfig.model,
maxTurns,
settingSources: ["project"],
allowedTools: ["Skill", "Read", "Glob", "Grep", "Bash", "Write", "Edit"],
env: {
...getQueryEnv(),
PATH: process.env.PATH ? `${stubBinDir}${delimiter}${process.env.PATH}` : stubBinDir,
WMILL_BENCHMARK_LOG_PATH: wmillLogPath,
},
};
await installWmillStub(stubBinDir);
for await (const message of query({ prompt, options })) {
if (message.type === "assistant") {
assistantMessageCount += 1;
const turnContext = anthropicUsageToBenchmarkTokenUsage(
message.message?.usage
)?.prompt;
if (turnContext && turnContext > 0) {
finalContextTokens = turnContext;
}
const content = message.message?.content;
if (Array.isArray(content)) {
for (const block of content) {
if (block.type === "tool_use") {
const input = normalizeToolInput(block.input);
toolsUsed.push({
tool: block.name,
input,
timestamp: Date.now()
});
if (block.name === "Skill") {
const skillInput = input as { skill?: string };
if (skillInput.skill) {
pushUnique(skillsInvoked, skillInput.skill);
}
}
if (block.name === "Bash") {
for (const command of extractBashCommands(input)) {
pushUnique(bashCommands, command);
}
}
} else if (block.type === "text") {
output += block.text;
}
}
}
} else if (message.type === "result") {
const resultMessage = message as { result?: string };
tokenUsage = extractCliResultTokenUsage(message) ?? tokenUsage;
if (typeof resultMessage.result === "string") {
output += resultMessage.result;
}
}
}
const proposedCommands = extractProposedWmillCommands(output);
const wmillInvocations = await readWmillInvocationLog(wmillLogPath);
return {
output,
durationMs: Date.now() - startedAt,
tokenUsage,
finalContextTokens,
trace: {
toolsUsed,
skillsInvoked,
assistantMessageCount,
bashCommands,
proposedCommands,
executedWmillCommands: wmillInvocations.map(formatExecutedWmillCommand),
wmillInvocations,
firstMutationToolIndex: getFirstMutationToolIndex(toolsUsed),
},
};
}
export function wasSkillInvoked(result: PromptRunResult, skillName: string): boolean {
return result.trace.skillsInvoked.some((skill) => skill === skillName);
}
export function wasToolUsed(result: PromptRunResult, toolName: string): boolean {
return result.trace.toolsUsed.some((tool) => tool.tool === toolName);
}
export function formatCliRunModelLabel(modelConfig: CliEvalModelConfig): string {
return `${modelConfig.provider}:${modelConfig.model}`;
}
export function getToolInputs(
result: PromptRunResult,
toolName: string
): Record<string, unknown>[] {
return result.trace.toolsUsed
.filter((tool) => tool.tool === toolName)
.map((tool) => tool.input);
}
export function extractProposedWmillCommands(output: string): string[] {
const commands: string[] = [];
for (const line of output.split(/\r?\n/)) {
for (const command of extractInlineBacktickCommands(line)) {
pushUnique(commands, command);
}
for (const command of extractInlineProseCommands(line.replace(/^\s*(?:[-*]|\d+\.)\s*/, ""))) {
pushUnique(commands, command);
}
}
return commands;
}
export function parseWmillInvocationLog(raw: string): CliWmillInvocation[] {
const entries: CliWmillInvocation[] = [];
const lines = raw.split(/\r?\n/);
for (let index = 0; index < lines.length; index += 1) {
if (lines[index] !== WMILL_LOG_MARKER) {
continue;
}
const timestamp = lines[index + 1] ?? "";
const cwd = lines[index + 2] ?? "";
const argCount = Number.parseInt(lines[index + 3] ?? "", 10);
if (!Number.isFinite(argCount) || argCount < 0) {
continue;
}
const start = index + 4;
const argv = lines.slice(start, start + argCount);
entries.push({ argv, cwd, timestamp });
index = start + argCount - 1;
}
return entries;
}
async function installWmillStub(binDir: string): Promise<void> {
await mkdir(binDir, { recursive: true });
const stubPath = join(binDir, "wmill");
const script = `#!/usr/bin/env bash
set -euo pipefail
{
printf '${WMILL_LOG_MARKER}\\n'
date -u +"%Y-%m-%dT%H:%M:%SZ"
printf '%s\\n' "$PWD"
printf '%s\\n' "$#"
printf '%s\\n' "$@"
} >> "\${WMILL_BENCHMARK_LOG_PATH:?}"
printf 'wmill benchmark stub: do not execute Windmill CLI commands during ai_evals; describe them in the final response instead.\\n' >&2
exit 97
`;
await writeFile(stubPath, script, "utf8");
await chmod(stubPath, 0o755);
}
async function readWmillInvocationLog(logPath: string): Promise<CliWmillInvocation[]> {
const raw = await readFile(logPath, "utf8").catch(() => null);
if (!raw) {
return [];
}
return parseWmillInvocationLog(raw);
}
function getQueryEnv(): Record<string, string> {
return Object.fromEntries(
Object.entries(process.env).flatMap(([key, value]) =>
typeof value === "string" ? [[key, value]] : []
)
);
}
function normalizeToolInput(input: unknown): Record<string, unknown> {
if (input && typeof input === "object" && !Array.isArray(input)) {
return input as Record<string, unknown>;
}
if (typeof input === "string") {
return { raw: input };
}
return {};
}
function extractBashCommands(input: Record<string, unknown>): string[] {
const commands: string[] = [];
for (const key of ["command", "cmd", "script", "raw"]) {
const value = input[key];
if (typeof value === "string") {
for (const line of value.split(/\r?\n/)) {
const command = normalizeCommandCandidate(line);
if (command) {
pushUnique(commands, command);
}
}
}
}
return commands;
}
function extractInlineBacktickCommands(line: string): string[] {
const commands: string[] = [];
const regex = /`(wmill [^`\n]+)`/g;
let match: RegExpExecArray | null = null;
while ((match = regex.exec(line)) !== null) {
if (hasNegatedCommandPrefix(line.slice(0, match.index))) {
continue;
}
const command = normalizeCommandCandidate(match[1]);
if (command) {
pushUnique(commands, command);
}
}
return commands;
}
function extractInlineProseCommands(line: string): string[] {
const commands: string[] = [];
let searchFrom = 0;
while (true) {
const inlineIndex = line.toLowerCase().indexOf("wmill ", searchFrom);
if (inlineIndex === -1) {
return commands;
}
if (!hasNegatedCommandPrefix(line.slice(0, inlineIndex))) {
const command = extractInlineProseCommandAt(line, inlineIndex);
if (command) {
pushUnique(commands, command);
}
}
searchFrom = inlineIndex + "wmill ".length;
}
}
function extractInlineProseCommandAt(line: string, startIndex: number): string | null {
const tokens = ["wmill"];
let cursor = startIndex + "wmill".length;
while (cursor < line.length) {
while (cursor < line.length && /\s/.test(line[cursor]!)) {
cursor += 1;
}
if (cursor >= line.length) {
break;
}
const current = line[cursor]!;
if ("`.,;:()[]{}".includes(current)) {
break;
}
const token = readCommandToken(line, cursor);
if (!token) {
break;
}
if (COMMAND_STOP_WORDS.has(token.value.toLowerCase())) {
break;
}
if (COMMAND_STOP_TOKENS.has(token.value)) {
break;
}
tokens.push(token.value);
cursor = token.nextIndex;
}
if (tokens.length <= 1) {
return null;
}
return normalizeCommandCandidate(tokens.join(" "));
}
function readCommandToken(
line: string,
startIndex: number
): { value: string; nextIndex: number } | null {
const firstChar = line[startIndex]!;
if (firstChar === `"` || firstChar === `'`) {
const endIndex = line.indexOf(firstChar, startIndex + 1);
const nextIndex = endIndex === -1 ? line.length : endIndex + 1;
return {
value: line.slice(startIndex, nextIndex),
nextIndex,
};
}
if (firstChar === "<") {
const endIndex = line.indexOf(">", startIndex + 1);
const nextIndex = endIndex === -1 ? line.length : endIndex + 1;
return {
value: line.slice(startIndex, nextIndex),
nextIndex,
};
}
let endIndex = startIndex;
while (endIndex < line.length && !/[\s`.,;:()[\]{}#]/.test(line[endIndex]!)) {
endIndex += 1;
}
if (endIndex === startIndex) {
return null;
}
return {
value: line.slice(startIndex, endIndex),
nextIndex: endIndex,
};
}
function hasNegatedCommandPrefix(prefix: string): boolean {
const normalizedPrefix = prefix
.toLowerCase()
.replace(/[`"'“”‘’]/g, " ")
.replace(/\s+/g, " ")
.trimEnd();
return NEGATED_COMMAND_PREFIX.test(normalizedPrefix);
}
function normalizeCommandCandidate(value: string): string | null {
const trimmed = value.trim().replace(/^`|`$/g, "");
if (!trimmed) {
return null;
}
const normalized = trimmed
.replace(/\s+/g, " ")
.replace(/[`.;:,]+$/g, "")
.trim();
return normalized.length > 0 ? normalized : null;
}
function formatExecutedWmillCommand(entry: CliWmillInvocation): string {
return ["wmill", ...entry.argv].join(" ").trim();
}
function getFirstMutationToolIndex(toolsUsed: ToolInvocation[]): number | null {
for (const [index, tool] of toolsUsed.entries()) {
if (tool.tool === "Write" || tool.tool === "Edit") {
return index;
}
if (tool.tool === "Bash" && extractBashCommands(tool.input).some(isLikelyMutatingBashCommand)) {
return index;
}
}
return null;
}
function isLikelyMutatingBashCommand(command: string): boolean {
return (
/\b(?:mkdir|touch|rm|mv|cp|install|tee)\b/.test(command) ||
/\b(?:cat|echo|printf)\b.*(?:>|>>|\|\s*tee\b)/.test(command) ||
/\bsed\s+-i\b/.test(command) ||
/\bperl\s+-pi\b/.test(command) ||
/\bwmill\b/.test(command)
);
}
function pushUnique(values: string[], value: string): void {
if (!values.includes(value)) {
values.push(value);
}
}