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.
npx skills add kingoo123/agent-harness-skills --skill agent-harnessgit clone --depth 1 https://github.com/kingoo123/agent-harness-skillsWrote 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.
[](https://agentmods.dev/skills/kingoo123/agent-harness-skills/agent-harness)<a href="https://agentmods.dev/skills/kingoo123/agent-harness-skills/agent-harness"><img src="https://agentmods.dev/badge/skills/kingoo123/agent-harness-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.
<a href="https://agentmods.dev/skills/kingoo123/agent-harness-skills/agent-harness"><img src="https://agentmods.dev/badge/skills/kingoo123/agent-harness-skills/agent-harness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.00891 |
| Opus 5 | $0.00034 | $0.00445 |
| Sonnet 5 | $0.00014 | $0.00178 |
| Haiku 4.5 | $0.00007 | $0.00089 |
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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Harness Design Skill
Purpose
Design reliable AI agents through harness engineering.
Do not treat the agent as a prompt only. Treat it as a system:
Agent = Model + Loop + Tools + Context + Memory + Permissions + Verification + Handoff
Use this skill when
- The user wants to design an AI agent.
- The user wants to convert a workflow into a reusable agent.
- The user wants to package an agent as an open-source skill.
- The user asks about tools, permissions, context, memory, verification, or subagents.
- The current agent design is vague, unsafe, untestable, or hard to maintain.
Required workflow
1. Identify the agent type
Classify the target agent:
- Coding agent
- Research agent
- Writing agent
- Customer support agent
- Data analysis agent
- Workflow automation agent
- Multi-agent system
- Domain-specific agent
2. Define the objective
Write one sentence:
This agent exists to ___ for ___ under ___ constraints.
3. Define the execution loop
Use this default loop unless the task requires another structure:
Observe → Plan → Act → Verify → Record → Continue / Stop
For each stage, specify:
- Inputs
- Allowed tools
- State updates
- Failure handling
- Stop conditions
4. Define tool contracts
For every tool, define:
tool:
name: string
purpose: string
input_schema: object
output_schema: object
permission_level: read_only | edit_safe | execute_safe | network_safe | admin
requires_approval: boolean
failure_modes:
- string
audit_log:
enabled: boolean
5. Define context layers
Use four layers:
Global Rules → Project Memory → Task State → Skill Context
For each layer, specify:
- What belongs here
- How it is loaded
- When it is summarized
- When it must not be stored
6. Define permissions
Default to least privilege.
Recommended levels:
read_only → read files, search, inspect
edit_safe → edit approved files only
execute_safe → run approved local commands
network_safe → call approved external APIs
admin → destructive or privileged actions; explicit human approval required
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.
- 12d ago First seen · 209 lines · 68 tokens per session scan A fe9f6ed34b39
agent-harness is a skill published in the GitHub repository kingoo123/agent-harness-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 68 tokens to every session and 891 once invoked, about $0.0003 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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