OpenAgents Control is a framework that adds plan-first, approval-based coding workflows to OpenCode, an AI coding framework. Developers and teams use it to make agents follow shared coding patterns, work across several programming languages, and validate changes through testing and review. The catalogue includes its agents, skills, commands, plugin, and hook.
Borrowing it
Nothing to install: this file belongs to darrenhinde/OpenAgentsControl. 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/darrenhinde/OpenAgentsControl/main/.opencode/command/context.mdgit clone --depth 1 https://github.com/darrenhinde/OpenAgentsControlWrote 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/commands/darrenhinde/openagentscontrol/context)<a href="https://agentmods.dev/commands/darrenhinde/openagentscontrol/context"><img src="https://agentmods.dev/badge/commands/darrenhinde/openagentscontrol/context/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/commands/darrenhinde/openagentscontrol/context"><img src="https://agentmods.dev/badge/commands/darrenhinde/openagentscontrol/context.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 | $0.00012 | $0.02068 |
| Opus 5.5 | $0.00005 | $0.00827 |
| Sonnet 5.5 | $0.00002 | $0.00414 |
| Haiku 4.5 | $0.00001 | $0.00207 |
Grade A, and why
context 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 — 310 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Manager
<critical_rules priority="absolute" enforcement="strict"> Files MUST be <200 lines. Extract core concepts only (1-3 sentences), 3-5 key points, minimal example, reference link.
<execution_priority> - Files <200 lines (@critical_rules.mvi_strict) - Show approval before cleanup (@critical_rules.approval_gate) - Function-based structure (@critical_rules.function_structure) - Load context before operations (@critical_rules.lazy_load) - Harvest (default), Extract, Organize, Update workflows - Cross-references, validation, navigation <conflict_resolution> Tier 1 always overrides Tier 2/3. </conflict_resolution> </execution_priority>
Arguments: $ARGUMENTS
Default Behavior (No Arguments)
When invoked without arguments: /context
Found 3 summary files:
📄 CONTEXT-SYSTEM-OVERVIEW.md (4.2 KB)
📄 SESSION-auth-work.md (1.8 KB)
📄 .tmp/NOTES.md (800 bytes)
Recommended action:
/context harvest - Clean up summaries → permanent context
Other options:
/context extract {source} - Extract from docs/code
/context organize {category} - Restructure existing files
/context help - Show all operations
```
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 · 310 lines · 12 tokens per session scan A 42bc98874c4f
context is a command published in the GitHub repository darrenhinde/OpenAgentsControl (4,910 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 2,068 once invoked, about $0.0000 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 2026-09-14.
Other commands, from other repositories
setup
Configure mnemonic for proactive memory operations.
ingest
A command for adding information to a file-based knowledge wiki from web pages, files, or text notes. It classifies the material, updates or creates wiki pages, and adds links between related pages.
learn
Command "learn" from datacore-one/datacore, covering /learn, purpose, when to use, usage and quick capture.
broadcast
Run broadcast on a distilled Raw — update related existing pages conversationally.
capture
Quickly save something as a single clean note in the right place — a link, a thought, an article, a snippet.
resume
Resume work from .claude/handoff/current.md in this fresh session (skip --resume).