Add Gemini extension skills#466
Conversation
|
CodeAnt AI is reviewing your PR. Thanks for using CodeAnt! 🎉We're free for open-source projects. if you're enjoying it, help us grow by sharing. Share on X · |
📝 WalkthroughWalkthroughThis PR introduces Desktop Commander MCP configuration and documentation: a new default rule preferring Desktop Commander MCP for filesystem, terminal, process, search, and workspace operations, paired with comprehensive skill documentation covering capabilities, example workflows, tool inventory, and operational conventions. ChangesDesktop Commander MCP Configuration & Documentation
Estimated code review effort🎯 1 (Trivial) | ⏱️ ~3 minutes Possibly related PRs
Suggested labels
Poem
🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
✏️ Tip: You can configure your own custom pre-merge checks in the settings. ✨ Finishing Touches🧪 Generate unit tests (beta)
Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out. Comment |
There was a problem hiding this comment.
Actionable comments posted: 1
🧹 Nitpick comments (1)
skills/desktop-commander-overview/SKILL.md (1)
80-80: ⚡ Quick winUse platform-neutral absolute-path examples.
/Users/<user>/Downloadsis macOS-specific and can cause wrong-path behavior on Linux/Windows. Consider a platform-neutral placeholder plusget_config-driven OS handling in the same example.Proposed doc tweak
-Resolve the path to absolute first (e.g., `/Users/<user>/Downloads`, not `~/Downloads`). Then `list_directory(path="/Users/<user>/Downloads", depth=1)` to see what's there. `start_search(pattern="*.pdf", path="/Users/<user>/Downloads", searchType="files")` and similar for other types. `create_directory` for new folders. `move_file` per item. Preview the move plan before executing destructive ops. +Resolve the path to an OS-correct absolute path first (e.g., `<absolute-downloads-path>`, not `~/Downloads`). Then `list_directory(path="<absolute-downloads-path>", depth=1)` to see what's there. `start_search(pattern="*.pdf", path="<absolute-downloads-path>", searchType="files")` and similar for other types. `create_directory` for new folders. `move_file` per item. Preview the move plan before executing destructive ops.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@skills/desktop-commander-overview/SKILL.md` at line 80, The docs use a macOS-specific example path (/Users/<user>/Downloads); change examples to a platform-neutral absolute-path placeholder (e.g., <absolute_path>/Downloads) and instruct resolving to an absolute path before calls, and mention using get_config or OS detection to map the placeholder to the actual OS-specific home directory. Update the example usage lines that reference list_directory(path=...), start_search(path=..., pattern=...), create_directory(...) and move_file(...) to use the placeholder and note resolving to absolute paths (and previewing the move plan) so the examples behave correctly on Linux/Windows/macOS.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In `@skills/desktop-commander-overview/SKILL.md`:
- Line 44: Update the documentation around the deploy flow to remove the example
of blindly sending "yes\n" via interact_with_process(pid, "yes\n") and instead
describe inspecting prompts from read_process_output, prompting the user for
explicit confirmation, and only calling interact_with_process with the confirmed
response; reference the existing examples using start_process,
read_process_output, and interact_with_process so readers know where to add a
prompt-inspection step and how to wire the explicit user confirmation into the
deploy session before sending any approval input.
---
Nitpick comments:
In `@skills/desktop-commander-overview/SKILL.md`:
- Line 80: The docs use a macOS-specific example path (/Users/<user>/Downloads);
change examples to a platform-neutral absolute-path placeholder (e.g.,
<absolute_path>/Downloads) and instruct resolving to an absolute path before
calls, and mention using get_config or OS detection to map the placeholder to
the actual OS-specific home directory. Update the example usage lines that
reference list_directory(path=...), start_search(path=..., pattern=...),
create_directory(...) and move_file(...) to use the placeholder and note
resolving to absolute paths (and previewing the move plan) so the examples
behave correctly on Linux/Windows/macOS.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: defaults
Review profile: CHILL
Plan: Pro
Run ID: 3cdf7bd9-aced-491b-b3c6-37f3b7e343bc
📒 Files selected for processing (2)
rules/desktop-commander-default.mdcskills/desktop-commander-overview/SKILL.md
|
|
||
| Before deploys, restarts, migrations, or other environment-changing commands, summarize the action and confirm with the user unless they already explicitly asked for that exact operation. | ||
|
|
||
| `start_process` for the deploy command (could be a script, an SSH-piped command, or `kubectl`/`gh` etc.). `read_process_output` to track output and surface errors. If the deploy needs an interactive confirmation, `interact_with_process(pid, "yes\n")`. The session stays alive while the agent watches for completion or rollback. |
There was a problem hiding this comment.
Avoid documenting blind yes confirmations in deploy flows.
Using interact_with_process(pid, "yes\n") as a generic pattern can approve unexpected prompts (including destructive ones). Recommend documenting prompt inspection + explicit user confirmation before sending any interactive approval input.
Proposed doc tweak
-`start_process` for the deploy command (could be a script, an SSH-piped command, or `kubectl`/`gh` etc.). `read_process_output` to track output and surface errors. If the deploy needs an interactive confirmation, `interact_with_process(pid, "yes\n")`. The session stays alive while the agent watches for completion or rollback.
+`start_process` for the deploy command (could be a script, an SSH-piped command, or `kubectl`/`gh` etc.). `read_process_output` to track output and surface errors. If the deploy needs an interactive confirmation, first show the exact prompt to the user and confirm intent, then send the precise approved response via `interact_with_process`. The session stays alive while the agent watches for completion or rollback.📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| `start_process` for the deploy command (could be a script, an SSH-piped command, or `kubectl`/`gh` etc.). `read_process_output` to track output and surface errors. If the deploy needs an interactive confirmation, `interact_with_process(pid, "yes\n")`. The session stays alive while the agent watches for completion or rollback. | |
| `start_process` for the deploy command (could be a script, an SSH-piped command, or `kubectl`/`gh` etc.). `read_process_output` to track output and surface errors. If the deploy needs an interactive confirmation, first show the exact prompt to the user and confirm intent, then send the precise approved response via `interact_with_process`. The session stays alive while the agent watches for completion or rollback. |
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@skills/desktop-commander-overview/SKILL.md` at line 44, Update the
documentation around the deploy flow to remove the example of blindly sending
"yes\n" via interact_with_process(pid, "yes\n") and instead describe inspecting
prompts from read_process_output, prompting the user for explicit confirmation,
and only calling interact_with_process with the confirmed response; reference
the existing examples using start_process, read_process_output, and
interact_with_process so readers know where to add a prompt-inspection step and
how to wire the explicit user confirmation into the deploy session before
sending any approval input.
|
CodeAnt AI finished reviewing your PR. |
User description
Summary by CodeRabbit
New Features
Documentation
CodeAnt-AI Description
Add Desktop Commander guidance for local files, terminals, and remote sessions
What Changed
Impact
✅ Faster local file and terminal tasks✅ Easier long-running process handling✅ Smoother SSH and large file workflows🔄 Retrigger CodeAnt AI Review
Details
💡 Usage Guide
Checking Your Pull Request
Every time you make a pull request, our system automatically looks through it. We check for security issues, mistakes in how you're setting up your infrastructure, and common code problems. We do this to make sure your changes are solid and won't cause any trouble later.
Talking to CodeAnt AI
Got a question or need a hand with something in your pull request? You can easily get in touch with CodeAnt AI right here. Just type the following in a comment on your pull request, and replace "Your question here" with whatever you want to ask:
This lets you have a chat with CodeAnt AI about your pull request, making it easier to understand and improve your code.
Example
Preserve Org Learnings with CodeAnt
You can record team preferences so CodeAnt AI applies them in future reviews. Reply directly to the specific CodeAnt AI suggestion (in the same thread) and replace "Your feedback here" with your input:
This helps CodeAnt AI learn and adapt to your team's coding style and standards.
Example
Retrigger review
Ask CodeAnt AI to review the PR again, by typing:
Check Your Repository Health
To analyze the health of your code repository, visit our dashboard at https://app.codeant.ai. This tool helps you identify potential issues and areas for improvement in your codebase, ensuring your repository maintains high standards of code health.