Borrowing it
Nothing to install: this file belongs to s-hiraoku/vscode-sidebar-terminal. 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/s-hiraoku/vscode-sidebar-terminal/main/.claude/commands/terminal-implement.mdgit clone --depth 1 https://github.com/s-hiraoku/vscode-sidebar-terminalWrote 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/s-hiraoku/vscode-sidebar-terminal/terminal-implement)<a href="https://agentmods.dev/commands/s-hiraoku/vscode-sidebar-terminal/terminal-implement"><img src="https://agentmods.dev/badge/commands/s-hiraoku/vscode-sidebar-terminal/terminal-implement/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/s-hiraoku/vscode-sidebar-terminal/terminal-implement"><img src="https://agentmods.dev/badge/commands/s-hiraoku/vscode-sidebar-terminal/terminal-implement.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 | $0.00008 | $0.01759 |
| Opus 5 | $0.00004 | $0.00879 |
| Sonnet 5 | $0.00002 | $0.00352 |
| Haiku 4.5 | $0.00001 | $0.00176 |
Grade A, and why
terminal-implement 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 8d 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Terminal Implementation Command
Research terminal implementation patterns and immediately implement the feature following VS Code best practices.
Execution Workflow
When this command is invoked (e.g., /terminal-implement Add terminal tab completion support):
Phase 1: Parallel Research (3 agents)
Launch all three research agents in parallel using a single message with multiple Task tool calls:
Agent 1: vscode-terminal-resolver
- Task description: "Analyze VS Code terminal implementation"
- Prompt: "Search the VS Code repository for how it implements: {ARGUMENTS}. Focus on terminal-related source code in src/vs/workbench/contrib/terminal/. Provide code references, implementation patterns, and key architectural decisions. Summary: 100-200 words."
Agent 2: serena-semantic-search
- Task description: "Search codebase semantically"
- Prompt: "Use Serena MCP to semantically search the current codebase for implementations related to: {ARGUMENTS}. Focus on TerminalManager, WebView managers, and xterm.js integrations. Identify existing patterns and architectural decisions. Provide file paths and line numbers. Summary: 100-200 words."
Agent 3: xterm-info-analyzer
- Task description: "Get xterm.js documentation"
- Prompt: "Retrieve xterm.js documentation and best practices for: {ARGUMENTS}. Include API references, configuration options, usage examples, and performance considerations. Summary: 100-200 words."
Phase 2: Implementation (1 agent)
After research agents complete, launch the implementation agent:
Agent 4: terminal-implementer
- Task description: "Implement terminal feature"
- Prompt: "Implement: {ARGUMENTS}
Research Findings:
VS Code Implementation: {vscode-terminal-resolver summary}
Current Codebase: {serena-semantic-search summary}
Xterm.js Best Practices: {xterm-info-analyzer summary}
Implementation Requirements:
- Follow TDD workflow: Write tests first (Red), implement (Green), refactor (Refactor)
- Use patterns from VS Code research findings
- Integrate with existing managers identified in codebase search
- Follow xterm.js best practices from documentation
- Maintain atomic operations and dispose handlers
- Provide file:line references in implementation
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.
- 8d ago First seen · 285 lines · 8 tokens per session scan A c25946c40667
terminal-implement is a command published in the GitHub repository s-hiraoku/vscode-sidebar-terminal (21 stars, last pushed 2d ago), licensed MIT. It adds 8 tokens to every session and 1,759 once invoked, about $0.0000 per session on Opus 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 2026-09-01.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.