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 SisyphusSQ/harness-template --skill issue-goal-promptgit clone --depth 1 https://github.com/SisyphusSQ/harness-templateWrote 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/sisyphussq/harness-template/issue-goal-prompt)<a href="https://agentmods.dev/skills/sisyphussq/harness-template/issue-goal-prompt"><img src="https://agentmods.dev/badge/skills/sisyphussq/harness-template/issue-goal-prompt/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/sisyphussq/harness-template/issue-goal-prompt"><img src="https://agentmods.dev/badge/skills/sisyphussq/harness-template/issue-goal-prompt.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 | $0.00040 | $0.00298 |
| Opus 5.5 | $0.00016 | $0.00119 |
| Sonnet 5.5 | $0.00008 | $0.00060 |
| Haiku 4.5 | $0.00004 | $0.00030 |
Grade A, and why
issue-goal-prompt 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 1mo 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
任务目标提示词
读取用户给出的任务、来源文档和工作仓库规则，提取目标、范围、关键约束与完成条件。来源可以是当前用户描述，不强制要求 Issue 标识。
只读与任务相关的计划或恢复摘要；已有事实优先引用，避免把整套规则和运行记录复制到新提示词。
提示词应包含：
- 目标与验收行为；
- 真实仓库、文件或接口入口；
- 用户明确的包含/排除范围和已授权动作；
- 必要实现步骤、验证入口及恢复条件。
参考 references/goal-prompt-template.md，按任务需要删去不适用字段，不发明执行模式或固定状态机。
用户要求交接文件，或需要跨会话恢复时，可保存到工作项目 .agents/state/；保留仍然有效的恢复信息。否则直接返回提示词，不因固定字符数自动创建文件。无 Issue 时使用清楚的任务主题命名。
生成提示词的授权不自动包含其描述的实施和外部动作；用户已明确要求继续执行时，遵循该授权，不因本技能再次暂停。
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.
- 1mo ago Changed · -33 lines · -12 tokens per session ecdbc2c4b8a4
- 2mo ago First seen · 56 lines · 52 tokens per session scan A 9581d1e8421d
issue-goal-prompt is a skill published in the GitHub repository SisyphusSQ/harness-template (11 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 298 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…