用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/Bradliebs/ollama-agent-harness --skill debugging命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Git workflow for the Ollama Agent Harness — atomic commits, small changes, safe history
Security hardening for the Ollama Agent Harness — input validation, command injection, secrets, deny-first review
Build a new MCP (Model Context Protocol) server from scratch — a stdio program that exposes tools to AI agents. Use when the user wants to wrap an API, CLI, or internal service as an MCP server the harness (or Claude Desktop, Cursor, etc.) can load. Adapted from anthropics/skills.
基于 SOC 职业分类
正在显示 SKILL.md
| name | debugging |
| description | Systematic debugging for the Ollama Agent Harness — reproduce, localize, reduce, fix, guard |
| domain | debugging |
| confidence | medium |
| source | authored for harness gap-fill |
| triggers | ["debug this","why does this fail","test is failing","fix the error"] |
Debugging skill for the Ollama Agent Harness. The harness runs local Ollama models with a simple agent loop, permission gating, and append-only sessions. Most bugs surface as failing Jest tests, broken tool dispatch, permission misfires, or context-budget regressions. Debug by evidence, not by guessing — a small local model cannot afford speculative edits.
testing skill) so the failure does not depend on a live model. No reproduction, no fix.core/ (loop), tools/ (dispatch), permissions/, context/, agents/, persistence/. Use code_graph callers <symbol> / code_graph callees <symbol> to trace the call path before reading files.When a build or test breaks, fix it before adding new behavior. Do not stack changes on a red bar.
For any directional bug (a ratio, signed margin, inequality, truncation threshold, off-by-one), write a one-line numeric trace showing the condition firing before editing. Prose like "it should truncate when too big" hides inverted comparisons.
Errors in tool dispatch must return as tool results for the model to adapt to. A catch that logs and continues silently hides the bug and the next failure.
it('recovers when a tool throws', async () => {
mockOllama.chat.mockResolvedValueOnce({
message: { role: 'assistant', tool_calls: [{ function: { name: 'bash', arguments: '{}' } }] },
done: true,
});
tool.execute = jest.fn().mockRejectedValue(new Error('boom'));
const events = [];
for await (const event of queryLoop(config)) events.push(event);
expect(events.some(e => e.type === 'tool_result' && e.result.error)).toBe(true);
});
code_graph callers dispatchTool
code_graph around checkPermission 1
try/catch that swallows the error instead of returning it as a tool result.