LongHorizon-Harness is a computer-use harness that lets AI agents continue work across desktop applications and the command line for extended periods by planning, acting, verifying, checkpointing, and recovering. It is for users who need Claude Code, Codex, OpenCode, or DeepSeek Harness to make reliable progress on complex long-running workflows without training a new model. The catalogue entries provide skills for operating this execution loop.
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 AMAP-ML/LongHorizon-Harness --skill analyze-trajgit clone --depth 1 https://github.com/AMAP-ML/LongHorizon-HarnessWrote 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/amap-ml/longhorizon-harness/analyze-traj)<a href="https://agentmods.dev/skills/amap-ml/longhorizon-harness/analyze-traj"><img src="https://agentmods.dev/badge/skills/amap-ml/longhorizon-harness/analyze-traj/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/amap-ml/longhorizon-harness/analyze-traj"><img src="https://agentmods.dev/badge/skills/amap-ml/longhorizon-harness/analyze-traj.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 | $0.00076 | $0.00252 |
| Opus 5 | $0.00038 | $0.00126 |
| Sonnet 5 | $0.00015 | $0.00050 |
| Haiku 4.5 | $0.00008 | $0.00025 |
Grade A, and why
analyze-traj 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.
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.
What it actually says
If only one task is issued, analyze it directly with instruction: analyze-single-traj.md.
If multiple tasks or a whole results directory are issued, use subagents to analyze them in parallel (one agent for each task). Do not analyze them sequentially by yourself. DO NOT tell it what to do. Just ask the subagent to analyze the task in target directory and use this skill (analyze-traj) to do the analysis. Pass any user instructions to every subagent.
After the per-task reports are ready:
- Do nothing but report to the user that the analysis is done and where to find the reports.
- Ask user if they want to synthesize a run-level summary, if yes use: analyze-full-run.md.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 13 lines · 76 tokens per session scan A 79cc891a00c5
analyze-traj is a skill published in the GitHub repository AMAP-ML/LongHorizon-Harness (1,492 stars, last pushed 21d ago), licensed MIT. It adds 76 tokens to every session and 252 once invoked, about $0.0004 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 2026-08-30.
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