agent-harness

agent-harness is a skill for Claude Code, Codex from humaisali/Awesome-AI-Skills. It costs 170 tokens per session (1,909 once invoked), scanned A, original, MIT.

A controlled process for running a group of coding skills as an agent loop: plan the work, perform each task, check the result, retry when needed, and escalate unresolved work.

In plain words
What is it for?
Use it to turn a clear goal into checked tasks, run domain-specific tools, apply limited retries, and stop only when checks pass or human help is needed.
Why use it?
It prevents an agent from declaring a task finished without verification and keeps track of what remains across sessions.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; mentions Claude Code.

Good fit Use it to turn a clear goal into checked tasks, run domain-specific tools, apply limited retries, and stop only when checks pass or human help is needed.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/humaisali/awesome-ai-skills/agent-harness
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add humaisali/Awesome-AI-Skills --skill agent-harness
Clone the repo
git clone --depth 1 https://github.com/humaisali/Awesome-AI-Skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for agent-harness

README.md
[![agentmods](https://agentmods.dev/badge/skills/humaisali/awesome-ai-skills/agent-harness/github.svg)](https://agentmods.dev/skills/humaisali/awesome-ai-skills/agent-harness)
Your own site
<a href="https://agentmods.dev/skills/humaisali/awesome-ai-skills/agent-harness"><img src="https://agentmods.dev/badge/skills/humaisali/awesome-ai-skills/agent-harness/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for agent-harness

Your own site · 80×15
<a href="https://agentmods.dev/skills/humaisali/awesome-ai-skills/agent-harness"><img src="https://agentmods.dev/badge/skills/humaisali/awesome-ai-skills/agent-harness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 170 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,909 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00170 $0.01909
Opus 5 $0.00085 $0.00955
Sonnet 5 $0.00034 $0.00382
Haiku 4.5 $0.00017 $0.00191

Measured 11d ago against content hash cc31a8a95072, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

agent-harness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/goal_compiler.py, scripts/harness_manifest_builder.py, scripts/loop_controller.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AI-ML & Data Science Skills/Agents & LLMs/agent-harness/SKILL.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Harness

You are a harness operator, not a hero. The loop — not your optimism — decides when work is done. Your job: compile the goal into tasks with checks, execute one task at a time, let the controller adjudicate verification, and stop when the state machine says stop.

The contract

GOAL → goal_compiler → PLAN → loop_controller: [execute → verify]* → CLOSE
                                     ↑______retry (≤ max_attempts, changed approach)
                                     └── ESCALATE on exhausted budgets — never fake success

Three layers, all JSON: a committed per-domain manifest (what skills/tools/checks exist), a per-goal plan (which tasks, which verifications, what "done" means), and a per-run state file (the single source of truth; a fresh session resumes from it alone).

Quick start

# 0. Pick the domain manifest (18 committed under assets/harnesses/, e.g. engineering-team.json)
ls assets/harnesses/

# 1. Compile the goal (refuses vague goals with exit 3 + forcing questions)
python3 scripts/goal_compiler.py \
  --goal "audit the payments service and design an SLO with an error budget" \
  --manifest assets/harnesses/engineering.json --out plan.json

# 2. Initialize the loop state
python3 scripts/loop_controller.py init --plan plan.json --state .agent-harness/state.json

# 3. Drive the loop — repeat until directive is "close" or "escalate"
python3 scripts/loop_controller.py next --state .agent-harness/state.json
#    → {"action": "execute", "task": "T1", ...}: open the task's skill (SKILL.md at
#      skill_path), do the work with its tools, then:
python3 scripts/loop_controller.py record --state .agent-harness/state.json \
  --task T1 --phase execute --exit-code 0
#    → the controller runs the task's checks ITSELF (subprocess, timeout, evidence log):
python3 scripts/loop_controller.py verify --state .agent-harness/state.json --task T1 --cwd <repo-root>

# 4. Close — refused (exit 4) while any task is unverified and unwaived
python3 scripts/loop_controller.py close --state .agent-harness/state.json

Read the full file on GitHub · 131 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 131 lines · 170 tokens per session scan A cc31a8a95072

Subscribe to this mod's changes

agent-harness is a skill published in the GitHub repository humaisali/Awesome-AI-Skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 170 tokens to every session and 1,909 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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