harness-integration

harness-integration is a skill for Claude Code from frankxai/Starlight-Intelligence-System. It costs 0 tokens per session (285 once invoked), scanned A, original, MIT.

Integration rules for connecting the ACOS Grok harness with repository instructions, skills, hooks, and other coding-agent tools.

In plain words
What is it for?
Use them to initialize sessions, enforce repository rules, delegate complex tasks, and run verification and quality checks.
Why use it?
They reduce setup mistakes by defining what to load at session start and which checks to run before changes are made.

Skill for Claude Code

Written for Claude Code: SessionStart hook event. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions subagents.

Part of the starlight-intelligence-system plugin — 6 skills, 121 commands, 7 agents shipped together

Good fit Use them to initialize sessions, enforce repository rules, delegate complex tasks, and run verification and quality checks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/frankxai/starlight-intelligence-system/harness-integration
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 frankxai/Starlight-Intelligence-System --skill harness-integration
Clone the repo
git clone --depth 1 https://github.com/frankxai/Starlight-Intelligence-System

Made for: Claude Code.

Or install starlight-intelligence-system, the plugin that ships this one along with the rest of its 6 skills, 121 commands, 7 agents.

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 harness-integration

README.md
[![agentmods](https://agentmods.dev/badge/skills/frankxai/starlight-intelligence-system/harness-integration/github.svg)](https://agentmods.dev/skills/frankxai/starlight-intelligence-system/harness-integration)
Your own site
<a href="https://agentmods.dev/skills/frankxai/starlight-intelligence-system/harness-integration"><img src="https://agentmods.dev/badge/skills/frankxai/starlight-intelligence-system/harness-integration/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 harness-integration

Your own site · 80×15
<a href="https://agentmods.dev/skills/frankxai/starlight-intelligence-system/harness-integration"><img src="https://agentmods.dev/badge/skills/frankxai/starlight-intelligence-system/harness-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 285 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 $0.00000 $0.00285
Opus 5 $0.00000 $0.00143
Sonnet 5 $0.00000 $0.00057
Haiku 4.5 $0.00000 $0.00028

Measured 6d ago against content hash 5df67a530211, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

harness-integration 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 6d ago.

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.

.grok/skills/harness-integration/SKILL.md · 19 lines

What it actually says

Grok Harness Integration (ACOS v10+)

Principles

  • Frank DNA in every response. God 99 via gates.
  • Shared catalog (~/.claude/skills + ~/.grok/skills + project .grok/) source of truth.
  • On start: echo excellence status, read GROK.md/CLAUDE.md/AGENTS.md (deeper wins).
  • Gates before edit: rules check, repo-mastery, plan-reviews, gstack qa (if web), santa/verification.
  • Subagent swarm + delegate: output exact claude/agy/gemini commands with injected rules for complex tasks.

Excellence Path (always)

repo-mastery → plan-*-review → verification-loop + santa-method → gstack (qa/browse/design/benchmark) → cso if needed → ship with evidence.

Composes with all ACOS skills (gstack 20+, content, dev, security). Use /skills in Grok TUI or natural language.

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. 6d ago First seen · 19 lines · 0 tokens per session scan A 5df67a530211

Subscribe to this mod's changes

harness-integration is a skill published in the GitHub repository frankxai/Starlight-Intelligence-System (8 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 285 tokens. 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 2026-09-03.

Related

Other skills, from other repositories

crewai-multi-agent

Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies…

davila7/claude-code-templates · 61 tokens

dispatch

Use when a task file exists in .hyperflow/tasks/ and workers need dispatching. Fans out parallel workers under per-batch Reviewers, runs a final integration review, and commits per sub-task. Endpoint of the auto-chain — no auto-deploy. Trigger with /hyperflow:dispatch, "run the plan", "execute the task", "build it"…

jeremylongshore/tons-of-skills-marketplace · 81 tokens

commonly

You are a member of a Commonly workspace — a shared space where humans and AI agents from any origin collaborate in pods (chat rooms with memory). Use this whenever you are connected to Commonly via the commonly MCP tools: to read what's happening, post, remember things across sessions, react, DM other agents, and…

Team-Commonly/commonly · 0 tokens

fabric-swarm

Creates a self-organizing team of persistent Pi Fabric actors with durable topics, mailboxes, and compare-and-swap tasks. Use for messenger-like collaboration and long-lived delegated work.

monotykamary/pi-fabric · 40 tokens

agent-team-handoff

A workflow for coordinating several AI assistants or agents on one project. It uses shared handoff files to record the current task, roles, decisions, progress, next steps, and proof of completion.

3338902669-ops/agent-orchestra · 179 tokens

dagr-producer

Emit and maintain a dagr run file — a live, contract-valid JSON description of recursive projects, tasks, attempts, gates, evidence, policies, events, and operator-message resolutions that dagr view renders as a DAG. Use when orchestrating agents or tracking multi-step work that a dagr pane should display.

aemrebarut/herdr-dagr · 70 tokens