Borrowing it
Nothing to install: this file belongs to asynkron/Asynkron.JsEngine. 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/asynkron/Asynkron.JsEngine/main/.claude/commands/duo.mdgit clone --depth 1 https://github.com/asynkron/Asynkron.JsEngineWrote 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/asynkron/asynkron.jsengine/duo)<a href="https://agentmods.dev/commands/asynkron/asynkron.jsengine/duo"><img src="https://agentmods.dev/badge/commands/asynkron/asynkron.jsengine/duo/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/asynkron/asynkron.jsengine/duo"><img src="https://agentmods.dev/badge/commands/asynkron/asynkron.jsengine/duo.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 | $0.00011 | $0.01395 |
| Opus 5.5 | $0.00004 | $0.00558 |
| Sonnet 5.5 | $0.00002 | $0.00279 |
| Haiku 4.5 | $0.00001 | $0.00139 |
Grade A, and why
duo 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 14d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Duo: Deep-Thinker + Coder Workflow
This command orchestrates a two-agent workflow for implementing GitHub issues.
Input Parsing
Parse the $ARGUMENTS to extract the issue number:
385→ issue number 385#385→ issue number 385https://github.com/asynkron/Asynkron.JsEngine/issues/385→ issue number 385
Extract the number and store as ISSUE_NUMBER.
Phase 1: Deep-Thinker Analysis
First, fetch the issue details:
gh issue view $ISSUE_NUMBER --json title,body,labels,comments
Then launch a deep-thinker agent with this prompt:
You are analyzing GitHub issue #$ISSUE_NUMBER for the Asynkron.JsEngine project.
## Issue Details
$ISSUE_CONTENT
## Your Task
1. **Research the codebase** to understand:
- What files and components are involved
- How similar features are implemented
- What tests exist for related functionality
- Any relevant patterns or conventions
2. **Analyze the issue** thoroughly:
- What is the root cause (for bugs) or requirements (for features)?
- What are the edge cases to consider?
- What could go wrong?
3. **Create an implementation plan** with:
- Step-by-step implementation approach
- Files to modify/create
- Tests to add
- Potential risks or blockers
4. **Post your plan as a GitHub comment** on issue #$ISSUE_NUMBER:
```bash
gh issue comment $ISSUE_NUMBER --body "$(cat <<'EOF'
# Implementation Plan
## Summary
[Brief description of the approach]
## Analysis Findings
[Key discoveries from codebase research]
## Implementation Steps
1. [Step 1]
2. [Step 2]
...
## Files to Modify
- `path/to/file.cs`: [what changes]
...
## Tests to Add
- [Test descriptions]
## Risks & Considerations
- [Any potential issues]
---
*Generated by /duo deep-thinker agent*
EOF
)"
Return the comment URL when done.
Wait for the deep-thinker agent to complete and capture the comment URL.
## Phase 2: Create Worktree
After deep-thinker completes, create a worktree for the coder:
```bash
git worktree add ../Asynkron.JsEngine-issue-$ISSUE_NUMBER -b feature/issue-$ISSUE_NUMBER
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.
- 14d ago First seen · 212 lines · 0 tokens per session scan A c3f5fad434e3
duo is a command published in the GitHub repository asynkron/Asynkron.JsEngine (11 stars, last pushed 3mo ago), licensed MIT. It adds 11 tokens to every session and 1,395 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 2026-10-02.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.