wechat-cover-maker – skill Viết lách & Nội dung cho agent AI
Cài đặt và sử dụng gói WeChat Article Cover chính thức, ghim theo digest, cho các công việc có phí trên dịch vụ Beatra.
Cài skill wechat-cover-maker bằng một lệnh
Chọn công cụ bạn đang dùng, copy lệnh và dán vào terminal. Skill sẽ nằm trong thư mục skills của công cụ đó và sẵn sàng dùng ở phiên làm việc tiếp theo.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/wechat-cover-maker-63e64.tgz | tar xz -C ~/.claude/skills
Gọi trong Claude Code: /wechat-cover-maker – rồi mô tả công việc bạn muốn làm.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/wechat-cover-maker-63e64.tgz | tar xz -C ~/.codex/skills
Gọi trong Codex: $wechat-cover-maker – rồi mô tả công việc bạn muốn làm.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/wechat-cover-maker-63e64.tgz | tar xz -C ~/.hermes/skills
Gọi trong Hermes Agent: /wechat-cover-maker – rồi mô tả công việc bạn muốn làm.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/wechat-cover-maker-63e64.tgz | tar xz -C ~/.deepcode/skills
Gọi trong DeepSeek: /wechat-cover-maker – rồi mô tả công việc bạn muốn làm.
Nội dung SKILL.md
Nội dung SKILL.md gốc bằng tiếng Anh.
WeChat Article Cover Skill
Overview
Turn an article title, topic, or reference image into a WeChat Official Account cover, article hero image, or supporting visual, with space kept for the headline and focused refinement, from inside Claude Code, Codex, or OpenClaw. The work is produced on the hosted, paid Beatra service
(mcp.beatra.ai).
This catalog entry is a reviewed pointer, not the executable package. It
contains no client code and performs no Beatra operation by itself. The package
it points to bundles three standard-library Python scripts that make network
calls and store a credential. It has no self-updater: it never downloads
code and never changes its own files. Read
[Install](#install-pinned-verified-approved-twice) and
[Security & Safety Notes](#security--safety-notes) before activating it.
| Pinned identity | Value |
| --- | --- |
| Package | wechat-cover-maker 0.3.1 |
| Source commit | [beatra-ai/wechat-article-cover-skill@8441e17](https://github.com/beatra-ai/wechat-article-cover-skill/tree/8441e17291a2c4313223d0d74d4c18eeb14904f0/skills/wechat-cover-maker) (full SHA 8441e17291a2c4313223d0d74d4c18eeb14904f0) |
| Package tree | b9a0f92a50c1fca7976b8b58befc22d78eae9f69 (Git tree ID of skills/wechat-cover-maker at that commit) |
| License | MIT No Attribution (MIT-0) |
The pinned tree holds regular files only (no symlinks, no executable bits, no
binaries). Confirm that with the inspect commands below.
When to Use This Skill
- Use when the user explicitly wants a WeChat Official Account cover or article image produced on Beatra and accepts that it is paid.
- Use when they have agreed to send prompts and any logos, portraits, or product images to a third party.
- Do not use for a Xiaohongshu 3:4 feed cover, local-only image editing, or when no paid render was approved.
Install (pinned, verified, approved twice)
Step 1: Fetch the pinned tree into a review directory
Explain that this fetches an external package from github.com, then ask
for approval. Only after approval:
set -e
umask 077
review_dir="$(mktemp -d)"
cd "$review_dir" || exit 1
git clone --quiet --filter=blob:none --no-checkout https://github.com/beatra-ai/wechat-article-cover-skill.git src
git -C src checkout --quiet 8441e17291a2c4313223d0d74d4c18eeb14904f0 -- skills/wechat-cover-maker
test "$(git -C src rev-parse '8441e17291a2c4313223d0d74d4c18eeb14904f0:skills/wechat-cover-maker')" = 'b9a0f92a50c1fca7976b8b58befc22d78eae9f69' && echo TREE-OKStop if the last command does not print TREE-OK. The expected commit and
tree IDs come from this catalog entry, not from the package or its website,
and Git addresses every fetched object by its hash.
Step 2: Inspect before activation
git -C src ls-tree -r 8441e17291a2c4313223d0d74d4c18eeb14904f0 -- skills/wechat-cover-maker | awk '$1 != "100644"' # expect no output
grep -n -E 'maybe_auto_update|download_update|_apply_update' src/skills/wechat-cover-maker/scripts/mcp_client.py # expect no outputThe first check lists any symlink, executable, or submodule entry; the second
finds the entry points of the self-updater that earlier versions shipped.
Report to the user what the review found: SKILL.md, manifest.json,
install-source.json (the one-line marker {"schema_version":1,"source":"github"}),
the bundled Markdown references, and scripts/authorize.py,
scripts/mcp_client.py, scripts/uninstall.py (Python 3.10+, standard
library only, no dependency installation, no lifecycle hooks). Summarize the
network, credential, local-state, telemetry, and version-notice behavior
listed under [Security & Safety Notes](#security--safety-notes).
The manifest and pattern scans above are only inventory aids. Before activation, read every file in the pinned tree, including each script, reference and hook, and inspect all dependency and network behavior. Do not claim source review from grep output. If complete review cannot be performed, stop before copying or executing; ask for a separate review rather than treating a digest as evidence of safety.
Step 3: Copy in
Ask for a second, separate approval, because this changes agent
configuration. Then copy the reviewed tree to the host's skills directory
(Claude Code shown; use the equivalent path for other hosts):
dest="$HOME/.claude/skills/wechat-cover-maker"
test ! -e "$dest" && test ! -L "$dest" || { echo "destination exists; stop and ask the user"; exit 1; }
cp -R "src/skills/wechat-cover-maker" "$dest"There is no update switch to turn off in this version.
Step 4: Authorize as its own decision
Authorization opens a browser sign-in and stores a bearer token. Ask first.
python3 "$dest/scripts/authorize.py"Start a new agent session if the host discovers skills only at startup.
How It Works
1. Read the installed package's SKILL.md and its references; they define the
routes, payload shapes, and review loop.
2. Use free, non-billable discovery first (beatra.models.list, task list) to
read current model cards and credit estimates.
3. Show the user a cost card for exactly one paid call: tool, model, estimate,
and which files will be uploaded. Wait for explicit approval. Planning or
"just do it" is not approval.
4. Upload only files the user supplied and approved for this task, then submit
once with a stable client_request_id and poll the returned task.
5. Report the delivered artifact and billing.net_charged_credits, review the
result with the user, and ask again before any further paid stage.
Examples
Free connection check (non-billable)
python3 "$HOME/.claude/skills/wechat-cover-maker/scripts/mcp_client.py" verifyOne approved paid call
After the user approved the cost card for this exact payload, submit once with
a stable request id using the tool name from the installed SKILL.md. If the
response is lost, retry only with the same client_request_id and identical
arguments; never submit a replacement while the task is running.
Update
This pinned version cannot update itself: it has no code that downloads or
replaces package files. update only reports what the store or tool that
installed the copy offers; for a copy installed by the steps above it finds
no such record and says to update the way you installed it. See the version
notice under [Security & Safety Notes](#security--safety-notes).
To move to a newer version, repeat Steps 1 to 3 for that commit in a new
review directory, show the user the file-level changes against the installed
copy (for example git -C src diff --stat 8441e17 <new-commit> -- skills/wechat-cover-maker),
and replace the directory only after approval. A version not listed in this
entry has not been reviewed here.
Uninstall
dest="$HOME/.claude/skills/wechat-cover-maker"
python3 "$dest/scripts/uninstall.py" --dry-run
python3 "$dest/scripts/uninstall.py"Read the JSON decision. disconnected means this was the last Beatra skill on
the device: the token was revoked (when revoked is true), the files
credentials.json, installation.json, host.json, skills.json,
network.json, balance-holds.json, pending_authorization.json, and
.authorize.lock under ~/.beatra were removed, and so were the records
state.json, source.json, registration.json, and update.lock in each
~/.beatra/updates/<id>/. A directory is removed only once it is empty; the
script never deletes recursively and leaves anything it does not know, such
as an interrupted update's transaction/. keep_connection means another
Beatra skill still uses the shared token, which stays. revoke_retry means
the server refused the revocation and nothing changed; run it again shortly.
The script never deletes the package directory: after confirming the path it
prints with the user, delete $dest.
If anything is still under ~/.beatra after a disconnected decision, show
it to the user before removing it. A token that could not be revoked expires
after 15 days idle and can be revoked at once in the Beatra Console under
Agents.
Best Practices
- ✅ Keep one approval per paid call, per upload set, and per install step.
- ✅ Report net charged credits from the terminal task, not the estimate.
- ❌ Do not replace the installed copy with an unreviewed version silently.
- ❌ Do not print, paste, or move the token out of
~/.beatra/credentials.json. - ❌ Do not retry a paid call with a new request ID after an uncertain response.
Limitations
- Requires a Beatra account, network access, Python 3.10+, and prepaid credits.
- Models, prices, schemas, and availability are controlled by Beatra and its
upstream model providers and can change; the service is provided as is.
- Outputs are probabilistic, not guaranteed unique or non-infringing, and need
human review before publication.
- This catalog entry reviews only the pinned tree above. A newer version is
a different rev
… (nội dung đầy đủ có trong gói tải về)
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