Open a browser tab so a human can highlight-and-comment on a Markdown file. Submits a structured JSON of comments the agent can read and respond to. Use when...
Browser
comment-md
Try itOpen a browser tab so a human can highlight-and-comment on a Markdown file. Submits a structured JSON of comments the agent can read and respond to. Use when...
What it does
Open a browser tab so a human can highlight-and-comment on a Markdown file. Submits a structured JSON of comments the agent can read and respond to. Use whenever the agent has generated a Markdown document (design doc, tech spec, README, PR description) and needs human review before proceeding.
The skill document
commentmd
When to invoke
- The user explicitly runs
/commentmd. - The agent has generated a Markdown document (design, tech spec, README, PR description, etc.) and needs targeted human feedback before iterating.
Usage
/commentmd
`` is a relative or absolute path to the Markdown file to review.
Agent execution steps
- Resolve `` to an absolute path
$ABS. - Run:
python3 ~/.agents/skills/commentmd/scripts/serve.py "$ABS" - The command starts a local HTTP server (
127.0.0.1:3118, or the next free port up to3128) and opens the browser. The user selects text, adds comments, then clicks 完成评论 (Finish). The command printswroteand exits. - Read `` — by default
.comments.jsonnext to the source file. - Process each comment:
quoteis the original excerpt;prefix/suffixare 32-char anchor windows around it;commentis the human's note. Ifmd_changed_during_reviewistrue, warn the user that the source file was modified externally between server start and submit. - Revise the original document based on the comments and summarize in the reply how each was addressed.
Headless / remote environments
Append --static /tmp/review.html:
python3 ~/.agents/skills/commentmd/scripts/serve.py "$ABS" --static /tmp/review.html
The user opens the HTML on their own machine; Finish downloads a JSON file. Ask the user for the downloaded file's path, then read it.
Output JSON format
{
"schema_version": 1,
"md_file": "/abs/path/plan.md",
"md_sha256": "abc...",
"md_changed_during_review": false,
"created_at": "2026-07-01T10:00:00Z",
"comment_count": 2,
"comments": [
{
"id": "c1",
"quote": "Store events in MySQL",
"prefix": "In our storage layer, we ",
"suffix": ", replicated across ...",
"comment": "Why not PostgreSQL? JSONB support is better.",
"created_at": "2026-07-01T10:00:12Z"
}
]
}
comment_count: 0 means the user has no objections.
Related skills
Open a browser tab so a human can highlight-and-comment on a Markdown file. Submits a structured JSON of comments the agent can read and respond to. Use when...
Turn Markdown files or folders into a polished, human-readable, self-contained HTML page by having the agent understand the document, choose an appropriate i...
Fetch any public web page and get back clean, LLM-ready markdown (polite, robots-respecting)
Retrieve only relevant sections from Markdown memory, project notes, decision logs, and heading-structured knowledge bases with the mdselect CLI. Use when Co...
Format and lint markdown files for consistency and readability. Use when Codex needs to normalize markdown documents, fix heading levels, standardize link fo...