1. Six-phase pipeline for creating Huawei Cloud skills — Socratic requirements gathering, CLI→SDK→API research, MD generation, test preparation, detailed testing, and final cleanup & compliance check 2. Phase-chained dependency: each phase builds on the previous phase's output, no phase may be skipped 3. Supports CLI, SDK, and REST API execution modes with automatic fallback detection 4. Generates complete skill directory structure with SKILL.md, references/, scripts/, templates/ 5. Validates against the Huawei Cloud Skill Specification (华为云Skill检查规范) Triggers include: "创建华为云Skill","新建华为云Skill","华为云skill创建器","创建 Skill","新建 Skill","skill 创建器","create skill","build skill","new skill","skill creator","scaffold a Huawei Cloud skill","wrap CLI or OpenAPI into a skill","package cloud operations into a skill","帮我创建华为云Skill","帮我新建一个Skill","封装华为云CLI为Skill","华为云Skill脚手架","帮我创建一个skill","我需要一个skill","建一个skill","生成skill","帮我建一个华为云skill".
文档
huawei-cloud-skill-tester
试用End-to-end functional testing framework for Huawei Cloud skills — three-tier pipeline covering single-skill unit testing, multi-skill orchestration, and end-to-end full flow testing. Each phase produces structured JSON output with chain verification. Supports skill installation validation, functional analysis, CLI→SDK→API feasibility research, test case generation, real-environment execution with resource lifecycle, resource cleanup, multi-skill scenario orchestration, trigger-conflict detection, and consolidated reporting. Triggers include: 测试技能, 执行技能测试, 跑测试流程, 技能回归测试, skill test, run skill tests, test huawei cloud skill, verify skill, 测试华为云skill, 全流程测试, 编排测试, 技能完整性检查, skill-tester, 跑测试, 回归测试, 组合测试, 多skill编排, verification, e2e.
它能做什么
End-to-end functional testing framework for Huawei Cloud skills — three-tier pipeline covering single-skill unit testing, multi-skill orchestration, and end-to-end full flow testing. Each phase produces structured JSON output with chain verification. Supports skill installation validation, functional analysis, CLI→SDK→API feasibility research, test case generation, real-environment execution with resource lifecycle, resource cleanup, multi-skill scenario orchestration, trigger-conflict detection, and consolidated reporting. Triggers include: 测试技能, 执行技能测试, 跑测试流程, 技能回归测试, skill test, run skill tests, test huawei cloud skill, verify skill, 测试华为云skill, 全流程测试, 编排测试, 技能完整性检查, skill-tester, 跑测试, 回归测试, 组合测试, 多skill编排, verification, e2e.
技能文档
Huawei Cloud Skill Tester — Three-Track Seven-Phase E2E Testing Pipeline
Independent, repeatable Huawei Cloud Skill testing framework. Does not depend on skill-creator; can test any existing Huawei Cloud Skill. Focuses on real-environment functional testing and multi-skill orchestration scenarios.
Overview
This Skill provides a three-track, seven-phase standardized testing pipeline:
| Tier | Phases | Goal |
|---|---|---|
| Tier 1: Single-Skill Unit Testing | Phase 0~4 | Verify each skill item by item: installation, feature extraction, technical research, test case generation, execution |
| Tier 2: Integration Testing | Phase 5~6 | Multi-skill orchestration scenario derivation + end-to-end real-environment flow verification |
| Tier 3: Final Report | Phase 7 | Consolidated report merging all phase outputs |
Core Design Principles
- Chain Verification — Before each Phase, check that the previous phase's JSON exists; if missing, refuse to execute
- Agent-proof — Write operations require user confirmation for each item; automatic gate bypassing is not allowed
- Three-Track Layering — Clear gates between Tiers; Tier 1 must be completed before entering Tier 2
- Batch Repeatable — Supports
--skills "skill-a,skill-b"or--all-installed - Fallback Strategy — When only 1 skill, Phase 5/6 automatically downgrade to single-skill lifecycle testing
- Standardized JSON Output — All phases output in a unified schema; Phase 7 merges into a single report
- Real-Environment First — All Tier 2 orchestrations execute against real Huawei Cloud; no mocks or simulations
Data Flow Diagram
User Input (--skills or --all-installed)
│
├── Tier 1 ──── Iterate over each skill ────
│ Phase 0 → 1 → 2 → 3 → 4
│ (phase-N-summary.json chain validation)
│
├── Tier 2 ──── Integration ────
│ Phase 5 (orchestration scenario derivation + real-environment execution)
│ Phase 6 (e2e full-flow: create→query→update→delete lifecycle)
│ Only 1 skill → Downgrade single-skill closed loop
│
└── Tier 3 ──── Final ────
Phase 7 (merge phase-0~6 JSON into consolidated report)
Prerequisites
- hcloud CLI installed and authenticated (for Tier 2 CLI mode testing) — Reference: https://support.huaweicloud.com/qs-hcli/hcli_02_003.html
- Python 3.8+ +
huaweicloudsdkpackages (for SDK mode testing) — SDK Reference: https://console.huaweicloud.com/apiexplorer/#/sdkcenter - Huawei Cloud AK/SK — 自动扫描所有以
HUAWEI/HW/HWC开头的环境变量,匹配其中含ACCESS_KEY/_AK/SECRET_KEY/_SK的键值对。If missing, must prompt the user to provide them; if the user does not provide, terminate the process. Strictly prohibited from skipping - Target Skill must be under $HOME/.hermes/skills/ or a user-specified path
- jq command (all JSON processing depends on it)
- API Reference: https://console.huaweicloud.com/apiexplorer/#/openapi
Workflow — Three-Track Seven-Phase
Tier 1: Single-Skill Unit Testing
Phase 0: Installation Verification (install/uninstall/reinstall)
Phase 1: Feature Extraction (metadata + commands + resource types)
Phase 2: Technical Research (CLI→SDK→API three-level availability)
Phase 3: Test Case Generation (functional cases TC-F + API cases TC-A)
Phase 4: Real-Environment Execution (read-only automatic + write operations require confirmation)
Tier 2: Integration Testing — Real-Environment Orchestration
Phase 5: Multi-Skill Orchestration (scenario derivation → step execution → state verification)
Phase 6: End-to-End Flow (resource lifecycle: create→query→update→delete)
Tier 3: Final Report
Phase 7: Consolidated Report (merge phase-0~6 JSON into single report)
Phase 0: Installation Verification
Goal: Verify whether the skill can be installed/uninstalled/reinstalled normally.
Steps:
- Check skill directory structure (SKILL.md exists, references/ exists)
- Confirm whether Hermes has the skill installed (check if a directory with the same name exists under $HOME/.hermes/skills/)
- Perform installation verification (simulated or actual installation)
- Perform uninstallation verification (simulated or actual uninstallation)
- Perform reinstallation verification (install → uninstall → install)
- Record installation duration, directory integrity, and installation status
# Simulated verification (directory structure check)
[ -f "${skill_path}/SKILL.md" ] && echo "SKILL.md exists"
[ -d "${skill_path}/scripts" ] && echo "scripts/ exists"
[ -d "${skill_path}/references" ] && echo "references/ exists"
# Installation status
hermes skills list | grep "${skill_name}"
echo $? # 0=installed, 1=not installed
Output: phase-0-summary.json
{
"install": {"status": "pass", "existing": true, "duration_s": 1.2},
"uninstall": {"status": "skipped", "reason": "not installed"},
"reinstall": {"status": "skipped", "reason": "not installed"},
"directory_integrity": {"pass": true, "checks": {...}}
}
Phase 1: Feature Extraction
Goal: Extract structured feature information from SKILL.md as input for all subsequent phases.
Steps:
- Read YAML frontmatter from SKILL.md → name, description, tags, triggers
- Extract core commands table (Core Commands section)
- Extract parameter confirmation table
- Identify feature types (query/create/modify/delete)
- Extract resource types involved (ECS instance, VPC, voucher, etc.)
- Note whether there are write operations (Create/Update/Delete)
- Read the list of test scripts under scripts/
- Read the list of reference files under references/
Output: phase-1-summary.json
{
"metadata": {
"name": "huawei-cloud-bss-voucher-manage",
"triggers": ["查代金券", "删除代金券", "list vouchers", ...],
"tags": ["huawei-cloud", "bss", "voucher"]
},
"capabilities": {
"list": ["查询代金券", "统计代金券"],
"create": [],
"update": [],
"delete": ["删除代金券"]
},
"has_write_operations": true,
"resource_types": ["bss_voucher"],
"commands": [
{"id": "CMD-01", "source": "SKILL.md", "description": "查询代金券列表", "executor": "sdk"},
{"id": "CMD-02", "source": "SKILL.md", "description": "统计代金券", "executor": "sdk"},
{"id": "CMD-03", "source": "SKILL.md", "description": "删除代金券", "executor": "sdk"}
],
"scripts": ["scripts/test-cli-commands.sh"],
"references": ["references/iam-policies.md", "references/api-paths.md"]
}
Phase 2: Technical Research
Goal: Perform CLI→SDK→API three-level fallback verification for each command extracted in Phase 1, determining the actual executable method.
Dependency: Phase 1 completed (phase-1-summary.json exists)
Research order (per command):
| Priority | Method | Verification |
|---|---|---|
| 1st | CLI | hcloud --cli-region=cn-north-4 --help |
| 2nd | SDK | python3 -c "from huaweicloudsdk{service}.v2 import ..." |
| 3rd | API | Only from SDK source _http_info or Huawei Cloud API Explorer |
Rule: API endpoints are strictly prohibited from being inferred; only allowed from SDK _http_info.resource_path or user confirmation from API Explorer.
Output: phase-2-summary.json
{
"research": [
{
"cmd_id": "CMD-01",
"description": "查询代金券列表",
"cli": {"available": false, "reason": "BSS not in hcloud service list"},
"sdk": {
"available": true,
"package": "huaweicloudsdkbss.v2",
"method": "list_sub_customer_coupons",
"api_path": "/v2/promotions/benefits/coupons"
},
"api": {"available": true, "endpoint": "/v2/promotions/benefits/coupons"},
"recommended_executor": "sdk",
"risk_level": "low"
}
]
}
Phase 3: Test Case Generation
Goal: Generate two types of test cases based on Phase 1+2, present them to the user for confirmation.
Dependency: Phase 1+2 completed (phase-1-summary.json + phase-2-summary.json exist)
Functional case division rules:
| Operation Type | Case Requirements | Risk Level |
|---|---|---|
| Query (List/Show/Get) | 1 positive + 1 boundary (limit=0 or empty filter) | low |
| Create | 1 standard + 1 parameter variant | high |
| Update | 1 verification that modification took effect | medium |
| Delete | 1 pre-deletion confirmation + 1 post-deletion verification | high |
| Statistics (count/aggregate) | 1 positive + 1 time range boundary | low |
Case IDs: TC-F-01 ~ TC-F-NN (functional), TC-A-01 ~ TC-A-NN (API/SDK)
Output: phase-3-summary.json
{
"functional_cases": [
{
"id": "TC-F-01",
"name": "List vouchers - positive",
"command": "list_sub_customer_coupons(limit=10)",
"expected": "Return voucher list, no more than 10 items",
"is_write": false,
"risk_level": "low",
"executor": "sdk",
"prerequisites": [],
"verification": "resp.count >= 0"
},
{
"id": "TC-F-03",
"name": "Delete voucher - positive",
"command": "reclaim_partner_coupons(coupon_id=...)",
"expected": "Voucher status changed to reclaimed",
"is_write": true,
"risk_level": "high",
"executor": "sdk",
"prerequisites": ["TC-F-01 (provide valid coupon_id)"],
"verification": "Query after delete to confirm status change"
}
],
"api_cases": [...]
}
Phase 4: Execution
Goal: Execute test cases from Phase 3 one by one; read-only runs automatically, write operations require per-case confirmation.
Dependency: Phase 3 completed (phase-3-summary.json exists)
Execution rules:
Pre-check: Is AK/SK set?
if AK/SK not set:
Prompt user to provide AK/SK
if user does not provide:
Terminate process, output "⛔ AK/SK missing, cannot execute tests"
else:
Set as environment variables, continue execution
Iterate over each test case:
if is_write == false:
Auto-execute → Record pass/fail
if is_write == true:
Show command and expected → Wait for user y/N confirmation
if confirmed:
Execute → Record pass/fail + resource changes
else:
Skip → Record skipped (user_cancelled)
Resource change record (key fields):
"resource_changes": [
{
"tc_id": "TC-F-03",
"resource_type": "bss_voucher",
"resource_id": "VCH-abc123",
"change_type": "deleted",
"cleanup_method": {"type": "sdk", "command": "already deleted, no cleanup needed"},
"cleanup_required": false
}
]
Output: phase-4-summary.json
{
"execution_results": [
{"tc_id": "TC-F-01", "status": "pass", "duration_s": 2.1, "output_snippet": "..."},
{"tc_id": "TC-F-03", "status": "pass", "duration_s": 1.5, "output_snippet": "...",
"resource_changes": [{"resource_type": "bss_voucher", "change_type": "deleted", ...}]}
],
"statistics": {"total": 10, "pass": 9, "fail": 0, "skip": 1},
"all_resources_changed": [...]
}
Phase 5: Multi-Skill Orchestration — Real-Environment Scenario Testing
Goal: Derive multi-skill business scenarios and execute them against the real Huawei Cloud environment to verify cross-skill integration.
Dependency: Phase 4 completed for all tested skills
Branch logic:
if skills_count == 1:
Downgrade to single-skill orchestration:
Extract all feature points from Phase 1
Sort by CRUD lifecycle (query → create → update → delete)
Execute sequentially against real environment
Verify each step's output feeds correctly into the next
if skills_count >= 2:
5a: Scenario derivation
- Group feature points by resource type from each skill's Phase 1 output
- Sort by dependency order (e.g., VPC must exist before ECS)
- Auto-generate scenario chains with resource passing between skills
- Present scenarios to user for confirmation
5b: Real-environment execution
- Execute each step in the confirmed scenario chain
- Pass resource IDs/outputs between steps as runtime context
- Record actual CLI/SDK output for each step
5c: Cross-skill data flow verification
- Verify output of skill A's operation can be consumed by skill B
- Check data format compatibility (JSON field mapping)
5d: Rollback on failure
- If any step fails, execute rollback steps for already-created resources
Auto-derivation example (ECS + VPC + EIP):
Input skills: [ECS-manage, VPC-manage, EIP-manage]
Derived scenario:
Step 1: VPC-manage.CreateVPC → outputs vpc_id
Step 2: ECS-manage.CreateECS (in vpc_id) → outputs instance_id
Step 3: EIP-manage.CreateEIP → outputs eip_id
Step 4: EIP-manage.BindEIP (bind to instance_id) → outputs binding_status
Step 5: ECS-manage.ListInstances (verify instance is running)
Step 6: EIP-manage.UnbindEIP (unbind from instance_id)
Step 7: ECS-manage.DeleteECS (instance_id)
Step 8: EIP-manage.ReleaseEIP (eip_id)
Step 9: VPC-manage.DeleteVPC (vpc_id)
Resource passing mechanism:
{
"runtime_context": {
"vpc_id": {"from_step": 1, "skill": "VPC-manage", "output_field": "vpc.id"},
"instance_id": {"from_step": 2, "skill": "ECS-manage", "output_field": "server.id"}
}
}
Execution mode: All steps run against real Huawei Cloud. Read-only steps (List/Show/Describe) run automatically. Write steps (Create/Delete/Update) require user confirmation for each step.
Output: phase-5-summary.json
{
"mode": "full" | "downgraded_single",
"scenario": {
"name": "VPC-ECS-EIP lifecycle",
"skills_involved": ["vpc-manage", "ecs-manage", "eip-manage"],
"steps": [
{"seq": 1, "skill": "vpc-manage", "action": "CreateVPC", "status": "pass", "output": {"vpc_id": "vpc-abc"}},
{"seq": 2, "skill": "ecs-manage", "action": "CreateECS", "status": "pass", "output": {"instance_id": "srv-xyz"}},
{"seq": 3, "skill": "eip-manage", "action": "CreateEIP", "status": "pass", "output": {"eip_id": "eip-123"}},
{"seq": 4, "skill": "eip-manage", "action": "BindEIP", "status": "pass", "output": {}},
{"seq": 5, "skill": "ecs-manage", "action": "ListInstances", "status": "pass", "output": {}},
{"seq": 6, "skill": "eip-manage", "action": "UnbindEIP", "status": "pass", "output": {}},
{"seq": 7, "skill": "ecs-manage", "action": "DeleteECS", "status": "pass", "output": {}},
{"seq": 8, "skill": "eip-manage", "action": "ReleaseEIP", "status": "pass", "output": {}},
{"seq": 9, "skill": "vpc-manage", "action": "DeleteVPC", "status": "pass", "output": {}}
]
},
"data_flow_verification": {"pass": true, "mismatches": []},
"rollback_required": false
}
Phase 6: End-to-End Flow Testing — Real-Environment Lifecycle
Goal: End-to-end verification of complete resource lifecycles against real Huawei Cloud, automatically deriving scenario chains from Phase 1 feature lists and executing them with real API calls.
Dependency: Phase 5 completed (phase-5-summary.json exists)
Branch logic:
if skills_count == 1:
Single-skill closed loop:
Sort all feature points by create→list→show→update→delete
Chain into a single-skill resource lifecycle
Execute each step via real CLI/SDK against production
Verify resource state after each mutation
if skills_count >= 2:
6a: Scenario derivation (from Phase 5 output)
- Use the confirmed scenario chain from Phase 5
- Extend with additional verification steps
6b: Lifecycle execution
- Execute each step against real Huawei Cloud environment
- Read-only steps auto-execute; write steps prompt user
6c: State consistency verification
- After each write operation, verify via read operation
- Confirm resource state matches expected
6d: Cross-step data validation
- Verify output schema compatibility between steps
- Detect field name mismatches, type mismatches
6e: Cleanup verification
- Verify all created resources are properly deleted
- Check for orphaned resources
Single-skill closed loop example (RDS query skill):
Steps:
Step 1: ListInstances (read-only, auto) → get instance count
Step 2: ShowInstanceDetail (if instance exists) → get instance config
Step 3: ListConfigurations (auto) → get parameter templates
Step 4: ShowBackupPolicy (if instance exists) → get backup config
Step 5: Analyze slow SQL (read-only, auto) → ListSlowLogs + ListTopSqls
Step 6: Parameter tuning recommendation (analysis, no API call)
Step 7: Backup strategy assessment (analysis, no API call)
Multi-skill E2E example (EC2 + EVS):
Steps:
Step 1: Create EVS volume → verify volume exists
Step 2: Attach volume to ECS instance → verify attachment
Step 3: Query volume metrics → verify I/O
Step 4: Detach volume → verify detached
Step 5: Delete volume → verify deleted
Output: phase-6-summary.json
{
"mode": "full" | "downgraded_single_skill_flow",
"scenario": {
"name": "RDS Intelligent Service Inspection",
"skills_involved": ["huawei-cloud-rds-intelligent-service"],
"steps": [
{"seq": 1, "action": "ListInstances", "status": "pass", "output_summary": "3 instances found"},
{"seq": 2, "action": "ShowInstanceDetail", "status": "pass", "output_summary": "instance config retrieved"},
{"seq": 3, "action": "ListConfigurations", "status": "pass", "output_summary": "5 templates found"},
{"seq": 4, "action": "ListDatastores", "status": "pass", "output_summary": "MySQL 8.0 available"},
{"seq": 5, "action": "ShowBackupUsage", "status": "pass", "output_summary": "2.3GB used"},
{"seq": 6, "action": "ListInstanceDiagnosis", "status": "pass", "output_summary": "No issues found"}
]
},
"state_consistency": {"pass": true},
"cleanup_verification": {"pass": true, "orphaned": []}
}
Phase 7: Consolidated Report
Goal: Merge Phase 0~6 JSON outputs into a single, comprehensive test report.
Dependency: Phase 0~6 all exist
Output: phase-7-summary.json
{
"test_id": "test-20260716-100300",
"phases_summary": [
{"phase": 0, "name": "install-check", "verdict": "pass", "duration_s": 3.5},
{"phase": 1, "name": "skill-analysis", "verdict": "pass", "duration_s": 12.0},
{"phase": 2, "name": "tech-research", "verdict": "pass", "duration_s": 45.0},
{"phase": 3, "name": "test-generation", "verdict": "pass", "duration_s": 8.0},
{"phase": 4, "name": "execution", "verdict": "pass", "duration_s": 120.0},
{"phase": 5, "name": "orchestration", "verdict": "pass", "duration_s": 200.0},
{"phase": 6, "name": "e2e-flow", "verdict": "pass", "duration_s": 180.0}
],
"overall_statistics": {
"total_phases": 7,
"pass": 7,
"fail": 0,
"skipped": 0,
"total_duration_s": 583.5,
"test_cases_total": 24,
"test_cases_pass": 22,
"test_cases_fail": 1,
"test_cases_skip": 1,
"orchestration_scenarios": 2,
"e2e_flows_executed": 1
},
"resources_created": 3,
"resources_cleaned": 2,
"resources_manual": 1,
"manual_interventions": [
{
"phase": 5,
"resource_type": "disk_volume",
"resource_id": "vol-xyz789",
"steps": ["hcloud EVS DeleteVolume --volume_id=vol-xyz789"]
}
],
"html_report": "reports/test-20260716-100300.html"
}
KooCLI Command Format Standard
This testing framework uses bash scripts as the primary execution mode, not direct hcloud CLI commands. However, when executing test cases, the framework constructs hcloud CLI commands in the following format:
hcloud --cli-region={region} [--param1=value1 ...]
Format Rules:
| Rule | Description |
|---|---|
| Service name | Follows KooCLI Services (uppercase: ECS, VPC, OBS; title case: CloudPond, IAMAccessAnalyzer) |
| Operation name | PascalCase (e.g., ListServersDetails, ListBuckets) |
| Region | Always include --cli-region={region} parameter |
| Parameters | Use --param=value syntax |
| Read-only limit | Always append --limit=1 for exploratory queries |
For OBS service, the framework uses hcloud obs (obsutil) subsystem:
hcloud obs [args...] [options...]
Core Commands
Full Pipeline Run
# Specify skills
bash scripts/run-test-pipeline.sh --skills "huawei-cloud-bss-voucher-manage"
# Specify multiple skills (comma-separated)
bash scripts/run-test-pipeline.sh --skills "huawei-cloud-bss-voucher-manage, huawei-cloud-ecs-manage"
# Scan all installed
bash scripts/run-test-pipeline.sh --all-installed
# Start from a specific phase (recovery scenarios only)
bash scripts/run-test-pipeline.sh --skills "bss-voucher" --phase 4
# Fresh mode
bash scripts/run-test-pipeline.sh --skills "bss-voucher" --fresh
Single Phase Run (Debug)
bash scripts/tier1/phase-0-install-check.sh --skill "huawei-cloud-bss-voucher-manage"
bash scripts/tier1/phase-1-skill-analysis.sh --skill "huawei-cloud-bss-voucher-manage"
bash scripts/tier2/phase-5-orchestration.sh --skills "skill-a, skill-b"
bash scripts/tier3/phase-7-final-report.sh --skills "skill-a, skill-b"
Run Multi-Skill Orchestration
# Derive and execute orchestration scenarios for 3 skills
bash scripts/tier2/phase-5-orchestration.sh --skills "ecs-manage, vpc-manage, eip-manage"
# Run E2E lifecycle test for a single skill
bash scripts/tier2/phase-6-full-flow.sh --skill "huawei-cloud-rds-intelligent-service"
Parameters
| Parameter | Required | Description | Example |
|---|---|---|---|
--skills | Mutually exclusive | Comma-separated skill names or directory names | "bss-voucher-manage, ecs-manage" |
--all-installed | Mutually exclusive | Scan all huawei-cloud-* under $HOME/.hermes/skills/ | — |
--phase | No | Start from a specific Phase (defaults to resume from missing phase) | --phase 0 |
--fresh | No | Delete all existing phase-*.json and start from scratch | — |
--output | No | Report output directory (default: reports/) | --output ./test-reports |
--skill-path | No | Skill directory path (default: $HOME/.hermes/skills/huawei-cloud/) | --skill-path ./skills |
References
references/architecture.md— Three-track seven-phase architecture diagram (Mermaid)references/output-schema-spec.md— Complete JSON field specification for each phasereferences/phase-transition-rules.md— Phase transition/fallback/skip rules
Output Format
All phases output phase-N-summary.json; Phase 7 merges them into a single report. See references/output-schema-spec.md for the JSON schema.
Phase 5 and 6 additionally output scenario execution logs with real CLI/SDK responses for auditability.
Best Practices
- Complete Tier 1 before entering Tier 2 to ensure skills are individually functional before orchestration
- Confirm write operations one by one in Phase 4 and Phase 5/6; do not batch-confirm to avoid misoperations
- With only 1 skill, Phase 5/6 automatically downgrade to single-skill closed loop; no need to manually skip
- When using
--freshto reset and rerun, confirm there are no uncleaned test resources - Review orchestration scenarios before execution to ensure resource dependency order is correct
Notes
- Three-track seven-phase strictly follows sequential order; chain verification prevents skipping
- API endpoints are strictly prohibited from being inferred; only obtain from SDK
_http_infoor API Explorer - Credentials are read from environment variables; hardcoding is prohibited
- If AK/SK is missing, must prompt the user to provide them; if the user does not provide, terminate the process. Strictly prohibited from skipping any step that requires credentials
- Resources created during testing must be tracked; if any are left behind, output manual cleanup instructions
- Orchestration scenarios are auto-derived; user should review and confirm before execution
- Write operations in orchestration scenarios require per-step user confirmation
Edge Cases
| Scenario | Handling |
|---|---|
| Skill directory does not exist | Report error and terminate, output available skill list |
| AK/SK environment variables not set | Prompt user to provide AK/SK; if user does not provide, terminate process, strictly prohibited from skipping |
| User specifies skill name but not installed in Hermes | --fresh performs directory-level detection; if not found, report error with guidance |
| Some Phase JSON files deleted | Chain detection → Restart from the deleted Phase |
| Network interruption during Phase 4 execution | Already executed case results are not lost; on rerun, skip passed cases (via --phase flag) |
| User hits Ctrl+C mid-execution | Already output phase JSON is valid; next time --resume will recover from the current phase |
| Only 1 skill under test | Phase 5 → single-skill orchestration, Phase 6 → single-skill closed loop |
| User unsatisfied with derived orchestration scenarios | User can manually edit the scenario or choose to skip it |
| Multi-skill scenario step fails midway | Execute rollback steps for already-created resources, report partial failure |
| Cross-skill data flow mismatch | Log field mapping details, suggest adapter/fix |
| Orphaned resources detected after E2E flow | List in report with manual cleanup instructions |
Design Principles
- Chain Verification — Each Phase checks the previous phase's JSON to prevent skipping
- Agent-proof — Write operations must be confirmed by the user; fake confirmations are not allowed
- Data-Driven — All phases output in JSON format; Phase 7 merges
- Batch Repeatable — The same set of skills can be tested repeatedly; --fresh resets
- Real-Environment First — All orchestrations and E2E flows execute against real Huawei Cloud; no mocks
- Degrade Without Losing Value — Single skill does not run empty orchestration phases; degrades to meaningful single-skill lifecycle tests
- Resource Safety — Resources created during testing must be tracked; if any remain, output clear manual cleanup instructions
- Credentials Mandatory — If AK/SK is missing, must prompt the user to provide; if not provided, terminate process. Strictly prohibited from skipping
相关技能
Audit Huawei Cloud skills for quality, security, and compliance using a two-check pipeline: skillspector (AI security) and gitleaks (credential leak). Generates structured reports with issue details and fix strategies. Triggers include: "审计技能","技能审计","检查技能质量","扫描技能问题","技能安全审计", "audit skill","check skill quality","scan skills for issues","skill audit", "华为云技能审计","技能合规检查","skill gate","质量门禁","技能检查", "audit huawei cloud skill","verify skill compliance","技能质量检查","跑审计","安全扫描".
按关键词或类目检索华为云技能目录,并安装匹配的技能。
用于测试 Skill 上传、识别、触发和基础输出链路。当用户要求“测试 skill 是否上传成功”“验证 skill 触发”“跑一遍上传测试”“upload test skill”时使用。该 Skill 只处理脱敏测试文本,不调用外部系统,不读取真实业务数据。
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"
Search, discover, browse and install AI Gallery Agent skills via natural language. Triggers include: "AI Gallery", "AI Gallery有什么skill", "有什么skill", "AI Gallery相关skill", "AI Gallery agent skill 市场", "AI Gallery skill类目", "skill 市场", "搜索AI Gallery skill", "安装skill", "订阅skill", "有没有XX skill", "有没有XX的能力", "帮我找 XX skill", "帮我找一个能XX的工具", "我想扩展功能", "介绍 XX Skill 内容", "XX Skill 具体做什么", "explore AI Gallery skills", "show AI Gallery skill categories", "does an AI Gallery skill exist for...", "which AI Gallery skills exist", "search skill", "find skill".
huaweicloud-skills-team 的更多技能
浏览全部技能用自然语言控制华为昇腾 NPU,本地或 SSH 远程执行 npu-smi 命令。
在华为云昇腾 910B DevServer 上按单机或双机(16 卡)拓扑部署并测试 LLM、VL、Embedding、Rerank 模型。
面向华为云资源的只读查询能力,用于资源清点、核对与参数发现。
通过本地 Python SDK 只读查询华为云 IAM 资源(用户、用户组、策略、委托、AK/SK、MFA、安全设置)。
在华为云 Flexus L 实例上一键部署 OpenClaw AI Agent 平台,并完成模型与通道配置。
在华为云 Flexus L 实例上一键部署 Hermes AI Agent 平台,并完成大模型与机器人通道配置。