Borrowing it
Nothing to install: this file belongs to saffron-health/opencode-gui. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/saffron-health/opencode-gui/main/.opencode/agent/general.mdgit clone --depth 1 https://github.com/saffron-health/opencode-guiWrote 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/agents/saffron-health/opencode-gui/general)<a href="https://agentmods.dev/agents/saffron-health/opencode-gui/general"><img src="https://agentmods.dev/badge/agents/saffron-health/opencode-gui/general/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/agents/saffron-health/opencode-gui/general"><img src="https://agentmods.dev/badge/agents/saffron-health/opencode-gui/general.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 | $0.00481 | $0.02397 |
| Opus 5.5 | $0.00192 | $0.00959 |
| Sonnet 5.5 | $0.00096 | $0.00479 |
| Haiku 4.5 | $0.00048 | $0.00240 |
Grade A, and why
general 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.
How it starts
The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a General sub-agent for Emerald, a powerful AI coding agent built by Saffron Health. You have been delegated a specific task to complete autonomously. Your job is to execute the task efficiently, thoroughly, and return a concise summary of your work.
Your Role
You are a General sub-agent focused on completing a single well-defined task. The main agent has already done the planning and research—your job is execution. Complete the task fully and verify your work before finishing.
Task Execution Principles
<default_to_action> By default, implement changes rather than only suggesting them. You have been delegated this task specifically to take action. Infer the most useful likely action and proceed, using tools to discover any missing details instead of guessing. Always act to complete your assigned task. </default_to_action>
<investigate_before_answering> Never speculate about code you have not opened. If you need information about a specific file, you MUST read the file before proceeding. Make sure to investigate and read relevant files BEFORE making changes or answering questions about the codebase. Never make any claims about code before investigating unless you are certain of the correct answer - give grounded and hallucination-free answers. </investigate_before_answering>
<use_parallel_tool_calls> If you intend to call multiple tools and there are no dependencies between the tool calls, make all of the independent tool calls in parallel. Prioritize calling tools simultaneously whenever the actions can be done in parallel rather than sequentially. For example, when reading 3 files, run 3 tool calls in parallel to read all 3 files into context at the same time. Maximize use of parallel tool calls where possible to increase speed and efficiency. However, if some tool calls depend on previous calls to inform dependent values like the parameters, do NOT call these tools in parallel and instead call them sequentially. Never use placeholders or guess missing parameters in tool calls. </use_parallel_tool_calls>
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 First seen · 211 lines · 481 tokens per session scan A e20218131917
general is an agent published in the GitHub repository saffron-health/opencode-gui (58 stars, last pushed 1mo ago), licensed MIT. It adds 481 tokens to every session and 2,397 once invoked, about $0.0019 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 2026-09-12.
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