Ivan Charapanau av

what makes a harness

an agentic harness is surprisingly simple. it's a loop that calls an llm, checks if it wants to use tools, executes them, feeds results back, and repeats. here's how each part works.

tools

the agent needs to affect the outside world. tools are just functions that take structured args and return a string. three tools is enough for a general-purpose coding agent:

const tools = {

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width, initial-scale=1">
	<title>tracequest — session</title>
	<style>

	:root {
	--bg: #111113;

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width, initial-scale=1">
	<title>tracequest — 019efdd4</title>
	<style>

	:root {
	--bg: #111113;

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width, initial-scale=1">
	<title>tracequest — 019efdd4</title>
	<style>

	:root {
	--bg: #111113;

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width, initial-scale=1">
	<title>tracequest — 019ef8af</title>
	<style>

	:root {
	--bg: #111113;

	<!doctype html>
	<html lang="en">
	<head>
	<meta charset="UTF-8" />
	<meta name="viewport" content="width=1920, height=1080" />
	<script src="https://cdn.jsdelivr.net/npm/gsap@3.14.2/dist/gsap.min.js"></script>
	<style>
	@import url("https://fonts.googleapis.com/css2?family=Inter:wght@400;700&family=JetBrains+Mono:wght@100;200;300;400;500;600;700;800&display=swap");

	* {

	lint-content:
	@command -v rg >/dev/null 2>&1 \|\| { echo >&2 "Error: rg (ripgrep) is missing. Please install it."; exit 1; }
	@rg --multiline --color=always -n -i -g '!.staged.md' -g '!.bak' \
	-e '—' \
	-e ';' \
	-e '\bdelve\b' \
	-e '\btapestry\b' \
	-e '\bleverage\b' \
	-e '\butilize\b' \
	-e '\bseamless(ly)?\b' \

	Read:
	https://github.com/agentskills/agentskills/blob/main/docs/specification.mdx
	https://github.com/agentskills/agentskills/blob/main/docs/integrate-skills.mdx
	Architect an implementation of agent skills for this codebase.

	I can think of a few requirements right away:

	Dedicated use-skill module
	A module instance per skill, i.e. each specific skill has is its own use-skill module instance in the workflow
	Only remote skills: from github, from URL, from storages

	curl --request POST \
	--url https://api.openai.com/v1/chat/completions \
	--header 'Accept: /' \
	--header 'Authorization: Bearer <API KEY>' \
	--header 'Content-Type: application/json' \
	--header 'User-Agent: httpyac' \
	--data '{
	"model": "gpt-4o",
	"messages": [
	{