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 oyi77/1ai-skills --skill agent-harness-optimizergit clone --depth 1 https://github.com/oyi77/1ai-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/oyi77/1ai-skills/agent-harness-optimizer)<a href="https://agentmods.dev/skills/oyi77/1ai-skills/agent-harness-optimizer"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/agent-harness-optimizer/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/oyi77/1ai-skills/agent-harness-optimizer"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/agent-harness-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.02500 |
| Opus 5 | $0.00019 | $0.01250 |
| Sonnet 5 | $0.00008 | $0.00500 |
| Haiku 4.5 | $0.00004 | $0.00250 |
Grade A, and why
agent-harness-optimizer 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 8d 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 — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Agent harness optimization is the practice of tuning the runtime environment that surrounds an AI agent -- model selection, prompt structure, hook configuration, memory persistence, and session management -- to maximize output quality while minimizing token cost and latency. Derived from real-world patterns across 10+ months of daily agentic work, these techniques apply to any harness: Claude Code, Cursor, OpenCode, Codex, Gemini, and beyond.
Anti-Rationalization Table
| Rationalization | Reality |
|---|---|
| "I'll figure it out as I go" | A structured approach saves time and reduces errors. Follow the workflow in this skill rather than improvising. |
| "I already know this topic" | Familiarity breeds shortcuts. Use the checklist to verify you haven't missed critical steps. |
| "This doesn't apply to my situation" | The patterns here generalize across contexts. Adapt, don't skip — the underlying principles hold. |
| "One more tool will fix it" | Adding complexity rarely solves process gaps. Master the core workflow first. |
When to Use
Trigger phrases:
-
"agent harness optimizer"
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"Token costs are rising faster than output quality"
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"Agents lose context between sessions or after compaction"
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"Hook scripts are slow, brittle, or produce noisy output"
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Token costs are rising faster than output quality
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Agents lose context between sessions or after compaction
-
Hook scripts are slow, brittle, or produce noisy output
-
You need the same agent behavior across multiple AI coding harnesses
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Session history grows unwieldy and needs structured management
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Background processes are eating into the main context window
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You want to set up continuous learning from session patterns
When NOT to Use
- Task is outside your authorization scope
- You need to implement controls (use implementing-* skills)
- Task is about analysis, not action (use analyzing-* skills)
- You don't have access to target systems
- Task requires compliance expertise (consult professionals)
- Task is about defense, not offense (use defensive skills)
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.
- 8d ago First seen · 265 lines · 38 tokens per session scan A f69c707a1231
agent-harness-optimizer is a skill published in the GitHub repository oyi77/1ai-skills (12 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 2,500 once invoked, about $0.0002 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 2026-09-03.
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