huawei-cloud-vod-collector

Invoke this skill to capture poor experiences and distill them into high-value requirements (Voice of Developer). Use when user encounters any Huawei Cloud related issues, like user expresses dissatisfaction, encounters errors, or wants to report issues/suggestions.Triggers include: "体验差","反馈问题","反馈建议","这个有bug","拒绝了请求","报告问题","反馈体验","report a problem","report a suggestion","bug report","poor experience","voice of developer"

huaweicloudskill@huaweicloudskill

Install

openclaw skills install @huaweicloudskill/huawei-cloud-vod-collector

VoD (Voice of Developer) Collector Skill

Script execution: All scripts are located in <SKILL_DIR>/scripts/. You must wrap every script execution with skill-quality-cli run --skill-name huawei-cloud-vod-collector -- (Mandatory mandate below); never run them bare. <SKILL_DIR> = directory containing this SKILL.md. .vod/ is relative to CWD (project working directory).

Overview

The VoD (Voice of Developer) Collector captures poor developer experiences and issues encountered while using Huawei Cloud tools or services. It prepares high-quality requirements or issue reports (GitCode issues) for product and engineering teams. The skill is declarative: it collects feedback with scripts and a hooks-based capture pipeline, deduplicates (in-session and cross-session), sanitizes, delivers prioritized issues to a GitCode repository, and can additionally fan a delivery notification out to a webhook or email channel.

Dependency: Quality telemetry is collected automatically via skill-quality-cli (installed by <SKILL_DIR>/scripts/ensure_cli.sh if absent; on Windows use <SKILL_DIR>/scripts/ensure_cli.ps1).

Core Commands

Common CLI examples grouped by function (all scripts under <SKILL_DIR>/scripts/):

Capture

bash

skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/md_io.py write-feedback --output .vod/feedbacks/
skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_sanitize.py file --path <file>

Extract / Edit (use write-feedback to update fields or edit feedback files directly)
Deliver

bash

skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py deliver --feedback-id <id> --feedbacks-dir .vod/feedbacks
skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py deliver --feedback-id <id> --feedbacks-dir .vod/feedbacks --force
skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py update-status --feedback-id <id> --status delivered --feedbacks-dir .vod/feedbacks

Cross-session dedup / notification

bash

skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py dedup-scan --feedbacks-dir .vod/feedbacks --feedback-id <id> --lookback 10 --json
skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py notify --feedbacks-dir .vod/feedbacks --feedback-id <id> --channel auto --json

Auto-login (only when deliver returns need_login)

bash

skill-quality-cli run --skill-name huawei-cloud-vod-collector -- bash <SKILL_DIR>/scripts/vod_install.sh
skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py server-start
skill-quality-cli run --skill-name huawei-cloud-vod-collector -- curl -s -X POST http://localhost:8080/login/start
skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py login-wait --session-id <session_id>
skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py server-stop --pid <pid>

Parameter Confirmation

The following parameters can be configured by users or integrators:

--feedbacks-dir / --output: Feedback storage directory. md_io.py write-feedback writes via --output; vod_deliver.py (deliver/update-status/dedup-scan/notify) reads via --feedbacks-dir. Both are usually passed as .vod/feedbacks/ — neither script defines a default, so each must be given explicitly (equivalent per-command naming).
--atomgit-home / ATOMCODE_HOME: AtomGit-GO configuration directory, default ~/.atomcode.
VOD_ATOMGIT_TOKEN: Environment-variable token override. When set to a non-empty value it takes precedence over ${ATOMCODE_HOME:-$HOME/.atomcode}/auth.toml, so no credential has to be persisted to disk.
delivery.channels.gitcode.repo_url: Target repository URL — read only from assets/config.yaml.
capture.dedup_window_sec: In-session deduplication window in seconds.
storage.max_feedbacks_per_session: Maximum stored feedbacks per session (default 5).
--lookback <N>: dedup-scan scan depth — the N most recently modified feedbacks (default 10).
--force / --skip-dedup: deliver duplicate-gate controls. --force delivers even when a strong cross-session duplicate candidate is found (and is also required to re-deliver a feedback whose delivery_status is already delivered, which otherwise returns already_delivered); --skip-dedup skips the pre-delivery duplicate scan entirely.
--channel webhook|email|auto: notify transport override (default auto → delivery.channels.notification.type).
--dry-run: notify lists the payloads that would be sent without sending anything.
Logging/Debug: Optional flags inside scripts to enable additional logging or debug modes.

Before delivery or auto-login, ensure the repo_url is provided via assets/config.yaml and is not inferred from git remote.

References

See additional implementation details and integration guides in the repository:

Prerequisites

Python dependencies

Install required Python packages before running any scripts:

bash

pip install -r <SKILL_DIR>/requirements.txt

Windows support

Windows is a supported platform (scripts/vod_install.ps1; the login server and its shutdown path use Windows process APIs such as taskkill).

The POSIX ownership/permission checks on auth.toml (owner uid via st_uid / os.getuid(), group/other write bits) are skipped when os.name == "nt" — on Windows the file is protected by the directory ACL instead. Older revisions raised AttributeError: module 'os' has no attribute 'getuid' and crashed (#959); deliver now returns its structured JSON result (success / need_login / error) on Windows as well.
Quality CLI install entry (#929): the official install_cli.sh maps only linux-x86_64 / linux-arm64 and the official manifest currently publishes only a linux-arm64 package, so Windows x86_64 had no supported entry. This skill adds a local cross-platform entry — scripts/install_cli.py plus scripts/ensure_cli.ps1, and a Windows branch in ensure_cli.sh — which installs the pure-Python fallback from the SHA256-verified official package when no native package exists. Always run it with PYTHONUTF8=1 / PYTHONIOENCODING=utf-8 (the entry scripts set both): the official cli_entry.py uses subprocess.run(..., text=True) without encoding, so Chinese Windows would decode child output as GBK and raise UnicodeDecodeError. See references/cli-installation-guide.md.

skill-quality-cli — ensured by bash <SKILL_DIR>/scripts/ensure_cli.sh (Linux/macOS, and Git Bash on Windows) or powershell -NoProfile -ExecutionPolicy Bypass -File <SKILL_DIR>\scripts\ensure_cli.ps1 (Windows PowerShell); idempotent, skips if present. Both export PYTHONUTF8=1 / PYTHONIOENCODING=utf-8, which is required on Chinese Windows (#929) — see references/cli-installation-guide.md.
- Upgrade: run skill-quality-cli upgrade manually (no auto-upgrade)
- Disable telemetry report: set SKILL_QUALITY_REPORT=0

**⚠️ Mandatory: every script execution in this skill MUST be wrapped with skill-quality-cli run --skill-name huawei-cloud-vod-collector -- (e.g. skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/md_io.py write-feedback ...) — bare invocations of python / md_io.py / vod_sanitize.py / vod_deliver.py / vod_install.* / curl are strictly forbidden. Disable telemetry (opt-out): SKILL_QUALITY_REPORT=0. Bootstrapping exception: the installers themselves — ensure_cli.sh / install_cli.sh / ensure_cli.ps1 / install_cli.py — may be executed bare (unwrapped) when skill-quality-cli is not yet installed; all other script executions must be wrapped once the CLI exists.

Workflow

Phase 1: Capture

Triggered by hooks (tool errors, user rejection, proactive reports). Generates raw feedback.

1.1 Generate Raw Feedback

Write the feedback file — skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/md_io.py write-feedback --output .vod/feedbacks/ (see --help for all params)
Sanitize — secrets are redacted automatically by write-feedback. To manually sanitize an existing file: skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_sanitize.py file --path <file>

1.2 Deduplication

In-session (during write): Same session_id + command + error_type within capture.dedup_window_sec → increment recurrence_count instead of writing a new file.
Cross-session (before Phase 3 delivery): scan the 10 most recent feedbacks and let the Agent (LLM) judge duplicates. Run:

bash

skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py dedup-scan --feedbacks-dir .vod/feedbacks --feedback-id <id> --lookback 10 --json

The command takes the most recently modified feedbacks (mtime, descending, --lookback default 10) and, for the given --feedback-id, reports the duplicate candidates: {"success":..., "scanned":N, "target":{...}, "candidates":[{id, file, session_id, feedback_type, error_type, status, delivery_status, recurrence_count, title, signature, signature_match, score, reason, is_strong_duplicate}], "strong_duplicates":[...], "should_deliver":true|false, "llm_prompt":"..."}. A candidate from a different session_id is reported when the normalized error-text signature matches or score ≥ 0.6; only signature-matching candidates whose peer is already closed out can block delivery. The Agent makes the final semantic call. On a match, do not deliver — merge into the existing feedback instead. See references/dedup-and-notify.md.

Phase 2: Extract

Note: This phase is executed by the Agent (LLM) directly — there is no independent extraction script (scripts/ intentionally contains no vod_extract.py or equivalent). The Agent enriches the feedback file using write-feedback to update fields.

Enrich feedback with context using LLM, then write all fields directly into the feedback file.

Each field maps to a specific section in the markdown file:

error_stack — Extract traceback/exit code from error context → ## Error Information → error_stack
user_intent — What the user wanted to do (e.g. "create OBS bucket"), NOT how → ## Context → user_intent
scenario — Reconstruct what the user was doing → ## User Report → scenario
expected_behavior — What the user expected. From dialog if explicit, otherwise infer from error → ## User Report → expected_behavior
product_name — Priority: annotation > agent_action > error_message → Title prefix 【Product】
environment — Platform, OS, session ID, Python version → ## Context → environment
dialog_context — 3-5 key turns around the problem point, preserve original language → ## Context → dialog_context

Use write-feedback again to update fields, or edit the markdown file directly.

Phase 3: Deliver

3.1 Sync to GitCode Issue

⚠️ repo_url comes only from assets/config.yaml → delivery.channels.gitcode.repo_url. Never use git remote, never ask the user.

Step 0 — cross-session dedup gate (required before delivering):

Run dedup-scan for the target feedback (see Phase 1.2) and inspect candidates + should_deliver.
If a candidate is the same problem (different session, and either a matching normalized error-text signature or score ≥ 0.6, semantically equivalent), do not deliver — update the existing feedback instead.
Otherwise deliver normally. deliver re-checks this gate: without --force it returns {"success":false,"error":"duplicate_suspected","duplicate_of":"<ID>","candidates":[...]} when a strong candidate exists — signature_match == true, a different session, and a peer already closed out (peer delivery_status == "delivered", or peer status in promoted/resolved; the status enum has no delivered value) — and no issue is created. Score-only candidates (signature_match == false) never block delivery. Re-run with --force only after the LLM has confirmed the candidate is a different problem; --skip-dedup skips the gate.

Single delivery — submit one feedback as a GitCode Issue:

bash

skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py deliver \
  --feedback-id <id> \
  --feedbacks-dir .vod/feedbacks

Update status — mark a feedback as delivered (or other status):

bash

skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py update-status \
  --feedback-id <id> --status delivered --feedbacks-dir .vod/feedbacks

Auto-login — when deliver returns "need_login": true, perform the following:

Pre-check (MCP shortcut — try first): Before starting the QR-code login flow below, check whether the devspace-connector MCP server exposes a gitcode_create_issue (or create_issue) tool. If the tool exists AND is callable, use it to create the issue directly — the deliver response now carries repo_url, issue_title, and issue_body for this purpose. After the MCP tool creates the issue, run update-status --status delivered and skip the QR-code login steps 1–8 below.

If the connector is unavailable — for ANY reason (server not connected, not configured, tool absent, or call fails): directly fall back to the QR-code login flow below. Do NOT ask the user whether to connect the MCP server or present any choice — proceed silently to step 1 of the fallback. Any attempt to "enable/connect the connector" is out of scope here and must NOT be offered as an option.

CRITICAL: Before installation, MUST tell the user:

This login uses the open-source project AtomGit-GO (MIT license).
Source: https://gitcode.com/weixin_45218422/AtomGit-GO

Check & install: Execute skill-quality-cli run --skill-name huawei-cloud-vod-collector -- bash <SKILL_DIR>/scripts/vod_install.sh (Linux/macOS) or skill-quality-cli run --skill-name huawei-cloud-vod-collector -- powershell <SKILL_DIR>/scripts/vod_install.ps1 (Windows).
Start server: skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py server-start → get pid from JSON output
Initiate QR login: skill-quality-cli run --skill-name huawei-cloud-vod-collector -- curl -s -X POST http://localhost:8080/login/start → get login_url, qr_code, session_id from JSON
Show QR to user: Display the login_url and ASCII qr_code. Say: "🔐 First-time login requires AtomGit authorization. Scan the QR code or open the URL in your browser."
Wait for authorization: skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py login-wait --session-id <session_id> — blocks until scanned (up to 60s). Do NOT ask the user whether they scanned; just wait.
On SCAN_SUCCESS, proceed to step 7.

CRITICAL: After successful authorization, MUST output the Security Notice:
- Security Notice: The AtomGit-GO login flow persists the token only to ${ATOMCODE_HOME:-$HOME/.atomcode}/auth.toml (owner-readable only, mode 0600). Anyone with file access can impersonate you — do not share this file.
- Note: Stored only in the local AI Shell environment. It will not be uploaded to any external server.
- Deletion: Manually delete the file, or it will be cleaned up when the environment resources are reclaimed.
Stop server: skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py server-stop --pid <pid>
Re-run the original deliver command.

Notification Channels (`notify`)

Optional fan-out of pending feedbacks to a webhook or an email recipient, in addition to the GitCode issue. Configure delivery.channels.notification in assets/config.yaml (ships enabled: false; enable it explicitly before use), then run:

bash

skill-quality-cli run --skill-name huawei-cloud-vod-collector -- python <SKILL_DIR>/scripts/vod_deliver.py notify --feedbacks-dir .vod/feedbacks --feedback-id <id> --channel auto --json

--channel webhook|email|auto (optional, default auto → delivery.channels.notification.type); --feedback-id limits the run to one feedback. --dry-run lists the payloads without sending.
Pending first: the command checks for pending feedbacks before anything else. With nothing pending it returns {"success":true,"pending":0,"sent":[]} without resolving the AtomGit token and without triggering the login flow — never prompt the user to log in just to learn there is nothing to send. Pending = not discarded, not already delivered, and no notified_at recorded yet; a successful send records notified_at under ## Delivery, so repeat runs stay idempotent.
webhook: HTTP POST with a JSON body to webhook.url, using webhook.headers. email: SMTP with TLS via email.smtp_host / email.smtp_port / email.recipients. Both honor retry_policy (max_retries, backoff_base_sec, backoff_max_sec).
Full JSON contract and configuration reference: references/dedup-and-notify.md.

Behavioral Constraints

Cancel: Clean up current file only. Never delete .vod/ or other records.
Decline: Skip silently, do not suppress future triggers.
Validation: Only product/service issues. No empty/minimal content ("test", "hello").
Cross-session dedup: run dedup-scan before deliver and skip delivery when the Agent judges a candidate to be the same problem; use deliver --force only after that judgment, and --skip-dedup only when the gate has deliberately been bypassed.
Session limit: Max storage.max_feedbacks_per_session (default 5). Exceeded → inform user.
Updates: In-place only. ID immutable. State machine: open → delivered → promoted → resolved or open → delivered → discarded (delivered is the post-delivery state written by update-status --status delivered).
Auto-init: .vod/ created on first use. Never overwritten.
Quality telemetry (mandatory): every script/command execution is wrapped with skill-quality-cli run --skill-name huawei-cloud-vod-collector --; disable via SKILL_QUALITY_REPORT=0 (opt-out).

Storage

Path: <CWD>/.vod/feedbacks/
Format: VOD-YYYYMMDD-NNNN.md

CLI Reference

Parameter	Description
`--atomgit-home <path>`	AtomGit-GO config dir (default: `~/.atomcode` or `$ATOMCODE_HOME`)
`--feedback-id <id>`	Feedback ID to deliver/update, or the target of `dedup-scan` / `notify`
`--feedbacks-dir <path>`	Path to `.vod/feedbacks/`
`--lookback <N>`	`dedup-scan`: number of most recent feedbacks to scan (default 10)
`--json`	Reserved for compatibility only — the code never reads it; `dedup-scan` / `notify` always print JSON
`--force`	`deliver`: deliver despite a strong cross-session duplicate candidate, or re-deliver an already delivered feedback
`--skip-dedup`	`deliver`: skip the pre-delivery duplicate scan
`--channel <webhook\|email\|auto>`	`notify`: transport override (default `auto`)
`--dry-run`	`notify`: list the payloads that would be sent without sending

KooCLI region

KooCLI invocations accept the global parameter --cli-region=<region> (e.g. hcloud ECS ListServers --cli-region=cn-north-4). In this skill all hcloud calls go through scripts/hcloud-run.sh, which injects --cli-region automatically from the HW_CLI_REGION environment variable when set (and the command does not already pass it).

Token Configuration

Token source, in priority order:
1. VOD_ATOMGIT_TOKEN environment variable — used directly when set to a non-empty value; auth.toml is not read and the token is never persisted to disk.
2. Token from open-source AtomGit-GO, saved in plaintext to ${ATOMCODE_HOME:-$HOME/.atomcode}/auth.toml.
Plaintext storage is upstream behavior (#114 问题 9). This skill cannot change how AtomGit-GO writes auth.toml; its mitigations are:
- POSIX: the parent directory must be owned by the current user and not group/other-writable; symlinks and non-regular files are refused; the file mode is tightened to 0600 before the token is read, and reading is refused when it cannot be tightened.
- Windows (os.name == "nt"): POSIX ownership/mode checks are skipped and the file is protected by the directory ACL instead.
- VOD_ATOMGIT_TOKEN avoids writing a credential to disk, which is a real improvement on shared hosts and containers — but on POSIX a same-uid process (including a child process) can still read the variable from /proc/<pid>/environ, so it is not a strict win; use a short-lived token when stronger isolation is required. Use --atomgit-home <path> to relocate auth.toml when it must be persisted.
- Anyone with read access to the file can impersonate you — do not share it.
Security Note (#114 问题 7): GitCode API v5 requires access_token as a URL query parameter, so the token may appear in proxy/load-balancer/server logs even though error responses are redacted. This is a GitCode API limitation this skill cannot work around, and VOD_ATOMGIT_TOKEN does not change it (the token still travels in the URL). Prefer short-lived tokens and a trusted egress path; migrate to a GitCode API version with header-based authentication when one is available.
Override: --atomgit-home <path>
Missing/expired → script returns "need_login": true → follow Phase 3.1 auto-login
Never write token to any file outside $ATOMCODE_HOME/auth.toml (or use VOD_ATOMGIT_TOKEN and write nothing at all)

huawei-cloud-vod-collector

Install

VoD (Voice of Developer) Collector Skill

Overview

Core Commands

Parameter Confirmation

References

Prerequisites

Python dependencies

Windows support

Workflow

Phase 1: Capture

1.1 Generate Raw Feedback

1.2 Deduplication

Phase 2: Extract

Phase 3: Deliver

3.1 Sync to GitCode Issue

Notification Channels (notify)

Behavioral Constraints

Storage

CLI Reference

KooCLI region

Token Configuration

Notification Channels (`notify`)