Borrowing it
Nothing to install: this file belongs to different-ai/opencode-scheduler. 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/different-ai/opencode-scheduler/main/AGENTS.mdgit clone --depth 1 https://github.com/different-ai/opencode-schedulerWrote 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/instructions/different-ai/opencode-scheduler/agents-md)<a href="https://agentmods.dev/instructions/different-ai/opencode-scheduler/agents-md"><img src="https://agentmods.dev/badge/instructions/different-ai/opencode-scheduler/agents-md/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/instructions/different-ai/opencode-scheduler/agents-md"><img src="https://agentmods.dev/badge/instructions/different-ai/opencode-scheduler/agents-md.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 | $0.01841 | $0.01841 |
| Opus 5.5 | $0.00736 | $0.00736 |
| Sonnet 5.5 | $0.00368 | $0.00368 |
| Haiku 4.5 | $0.00184 | $0.00184 |
Grade A, and why
opencode-scheduler AGENTS.md 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 2mo 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 — 348 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent-Native Architecture: Implementation Guide
A practical reference for building applications where agents are first-class citizens.
Core Principles
1. Parity
Whatever the user can do through the UI, the agent must be able to achieve through tools.
Create a capability map:
| User Action | Agent Method |
|---|---|
| Create item | write_file or create_item tool |
| Update item | update_file or update_item tool |
| Delete item | delete_file or delete_item tool |
| Search | search_files or search tool |
Test: Pick any UI action. Can the agent accomplish it?
2. Granularity
Prefer atomic primitives. Features are outcomes achieved by an agent in a loop.
# Wrong - logic in code
Tool: classify_and_organize_files(files)
# Right - agent decides
Tools: read_file, write_file, move_file, list_directory, bash
Prompt: "Organize downloads by content and recency"
Test: To change behavior, do you edit prose or refactor code?
3. Composability
New features = new prompts (when tools are atomic and parity exists).
Prompt: "Review files modified this week. Summarize changes. Suggest three priorities."
No code written. Agent uses list_files, read_file, and judgment.
4. Emergent Capability
Agent can accomplish things you didn't explicitly design for.
Build atomic tools → Users ask unexpected things → Agent composes solutions → You observe patterns → Optimize common patterns → Repeat.
Tool Design
Domain Tools
Add when needed for:
- Vocabulary anchoring -
create_noteteaches "note" concept better than "write file with format" - Guardrails - Validation that shouldn't be left to agent judgment
- Efficiency - Common multi-step operations
Rule: One conceptual action per tool. Judgment stays in prompts.
# Wrong
analyze_and_publish(input) # bundles judgment
# Right
publish(content) # one action, agent decided what to publish
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.
- 2mo ago First seen · 348 lines · 1,841 tokens per session scan A 2d45e2d6971d
opencode-scheduler AGENTS.md is an instructions file published in the GitHub repository different-ai/opencode-scheduler (517 stars, last pushed 8mo ago), licensed MIT. It adds 1,841 tokens to every session, about $0.0074 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.
opencode-scheduler AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| opencode-scheduler AGENTS.mddifferent-ai/opencode-scheduler | Instructions file | 517 | 8mo ago | MIT | A | 1,841 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |