qwencloud-text

SKILL.md

Agent setup: If your agent doesn't auto-load skills (e.g. Claude Code), see agent-compatibility.md once per session.

Qwen Text Chat (OpenAI-Compatible)

Generate text, conduct conversations, write code, and invoke tools using Qwen models through the OpenAI-compatible API. This skill is part of qwencloud/qwencloud-ai.

Skill directory

Use this skill's internal files to execute and learn. Load reference files on demand when the default path fails or you need details.

Location Purpose
scripts/text.py Default execution — chat/completions request, streaming, output save
references/execution-guide.md Fallback: curl, Python SDK, function calling, thinking mode
references/api-guide.md API supplement and full code examples
references/prompt-guide.md Prompt engineering: CO-STAR framework, CoT, few-shot, task steps
references/sources.md Official documentation URLs (manual lookup only)
references/agent-compatibility.md Agent self-check: register skills in project config for agents that don't auto-load

Security

NEVER output any API key or credential in plaintext. Always use variable references ($DASHSCOPE_API_KEY in shell, os.environ["DASHSCOPE_API_KEY"] in Python). Any check or detection of credentials must be non-plaintext: report only status (e.g. "set" / "not set", "valid" / "invalid"), never the value. Never display contents of .env or config files that may contain secrets.

When the API key is not configured, NEVER ask the user to provide it directly. Instead, help create a .env file with a placeholder (DASHSCOPE_API_KEY=sk-your-key-here) and instruct the user to replace it with their actual key from the QwenCloud Console. Only write the actual key value if the user explicitly requests it.

Key Compatibility

Scripts require a standard QwenCloud API key (sk-...). Coding Plan keys (sk-sp-...) cannot be used for direct API calls — they are designed exclusively for interactive coding tools (Cursor, Claude Code, Qwen Code) and do not work on QwenCloud API endpoints. The script detects sk-sp- keys at startup and prints a warning. If qwencloud-ops-auth is installed, see its references/codingplan.md for details on key types, endpoint mapping, and error codes.

Model Selection

Model Use Case
qwen3.5-plus Recommended default — balanced performance, cost, speed, 1M context
qwen3.5-flash Fast, low-cost, 1M context
qwen3-max Strongest capability
qwen-plus General purpose
qwen-turbo Cheapest, low latency
qwen3-coder-next Recommended code model — best balance of quality, speed, cost; agentic coding
qwen3-coder-plus Code generation — highest quality for complex tasks
qwen3-coder-flash Code generation — fast responses, lower cost
qwq-plus Reasoning / chain-of-thought
qwen-mt-plus Machine translation — best quality, 92 languages
qwen-mt-flash Machine translation — fast, low cost, 92 languages
qwen-mt-lite Machine translation — real-time chat, fastest, 31 languages
qwen-plus-character-ja Role-playing — recommended for Singapore
qwen-plus-character Role-playing — character restoration, empathetic dialog
qwen-flash-character Role-playing — fast, lower cost
  1. User specified a model → use directly.
  2. Consult the qwencloud-model-selector skill when model choice depends on requirement, scenario, or pricing.
  3. No signal, clear taskqwen3.5-plus (default).

Fallback: if model-selector is unavailable, the defaults in the table above apply.

⚠️ Important: The model list above is a point-in-time snapshot and may be outdated. Model availability changes frequently. Always check the official model list for the authoritative, up-to-date catalog before making model decisions.

Execution

Prerequisites

  • API Key: Check that DASHSCOPE_API_KEY (or QWEN_API_KEY) is set using a non-plaintext check only (e.g. in shell: [ -n "$DASHSCOPE_API_KEY" ]; report only "set" or "not set", never the key value). If not set: run the * qwencloud-ops-auth* skill if available; otherwise guide the user to obtain a key from QwenCloud Console and set it via .env file (echo 'DASHSCOPE_API_KEY=sk-your-key-here' >> .env in project root or current directory) or environment variable. The script searches for .env in the current working directory and the project root. Skills may be installed independently — do not assume qwencloud-ops-auth is present.
  • Python 3.9+ (stdlib only, no pip install needed for script execution)

Environment Check

Before first execution, verify Python is available:

python3 --version  # must be 3.9+

If python3 is not found, try python --version or py -3 --version. If Python is unavailable or below 3.9, skip to * Path 2 (curl)* in execution-guide.md.

Default: Run Script

Script path: Scripts are in the scripts/ subdirectory of this skill's directory (the directory containing this SKILL.md). You MUST first locate this skill's installation directory, then ALWAYS use the full absolute path to execute scripts. Do NOT assume scripts are in the current working directory. Do NOT use cd to switch directories before execution.

Execution note: Run all scripts in the foreground — wait for stdout; do not background.

Discovery: Run python3 <this-skill-dir>/scripts/text.py --help first to see all available arguments.

python3 <this-skill-dir>/scripts/text.py \
  --request '{"messages":[{"role":"user","content":"Hello!"}],"model":"qwen3.5-plus"}' \
  --output output/qwencloud-text/ --print-response

For streaming (recommended for interactive use):

python3 <this-skill-dir>/scripts/text.py \
  --request '{"messages":[{"role":"user","content":"Write a poem about the sea"}],"model":"qwen3.5-plus"}' \
  --stream --print-response
Argument Description
--request '{...}' JSON request body
--file path.json Load request from file (alternative to --request)
--stream Enable streaming output
--output dir/ Save response JSON to directory
--print-response Print response to stdout
--model ID Override model (also settable in request JSON)

Verify Result

  • Exit code 0 + output contains valid JSON with choices field → success
  • Non-zero exit, HTTP error, empty response, or JSON with "code"/"message" error → fail
  • If agent cannot read exit codes, scan output for error patterns (Error, Traceback, 401, 403)
  • Post-execution check: When --output is used, verify the response JSON file exists and contains choices
  • MANDATORY — stderr signal check: After confirming the result, scan the command's stderr output for [ACTION_REQUIRED] or [UPDATE_AVAILABLE]. If either signal is present, you MUST follow the instructions in Update Check below before responding to the user.

On Failure

If the script fails, match the error output against the diagnostic table below to determine the resolution. If no match, read execution-guide.md for alternative paths: curl commands (Path 2), Python SDK code generation (Path 3), and autonomous resolution (Path 5).

If Python is not available at all → skip directly to Path 2 (curl) in execution-guide.md.

Error Pattern Diagnosis Resolution
command not found: python3 Python not on PATH Try python or py -3; install Python 3.9+ if missing
Python 3.9+ required Script version check failed Upgrade Python to 3.9+
SyntaxError near type hints Python < 3.9 Upgrade Python to 3.9+
QWEN_API_KEY/DASHSCOPE_API_KEY not found Missing API key Obtain key from QwenCloud Console; add to .env: echo 'DASHSCOPE_API_KEY=sk-...' >> .env; or run qwencloud-ops-auth if available
HTTP 401 Invalid or mismatched key Run qwencloud-ops-auth (non-plaintext check only); verify key is valid
SSL: CERTIFICATE_VERIFY_FAILED SSL cert issue (proxy/corporate) macOS: run Install Certificates.command; else set SSL_CERT_FILE env var
URLError / ConnectionError Network unreachable Check internet; set HTTPS_PROXY if behind proxy
HTTP 429 Rate limited Wait and retry with backoff
HTTP 5xx Server error Retry with backoff
PermissionError Can't write output Use --output to specify writable directory

Quick Reference

Request Fields

Field Type Description
prompt / messages string | array User input or message list
model string Model ID (e.g. qwen3.5-plus)
system string System prompt (optional)
temperature float 0–2, controls randomness
max_tokens int Max output tokens
tools array Function definitions for tool calling
stream bool Enable streaming (recommended for interactive use)
enable_thinking bool Enable thinking mode. Model defaults apply: qwen3.5-plus/qwen3.5-flash have thinking ON by default. Only set explicitly when user requests deep thinking or needs to disable for flash models. Adds latency for real-time tasks.

Response Fields

Field Description
text Generated text content
model Model used
usage Token usage (prompt_tokens, completion_tokens)
tool_calls Function call requests (if tools used)

Advanced Features

These are API-level features supported through request parameters. All use the same chat/completions endpoint.

Feature How to Enable Notes
Structured output response_format: {"type": "json_schema", "json_schema": {...}} Force JSON output conforming to schema
Web search enable_search: true Real-time web search augmented responses
Deep thinking enable_thinking: true Extended reasoning; only when user requests it
Function calling tools: [...] Define functions for tool use
Context cache Automatic for repeated prefixes; or explicit session-based Reduces cost for repeated context
Partial mode partial_mode: "prefix" Continue/complete a prefix
Batch inference Async batch API with JSONL input 50% cost discount

For detailed usage of each feature, see api-guide.md and sources.md.

Error Handling

Error Cause Action
401 Unauthorized Invalid or missing API key Run qwencloud-ops-auth if available; else prompt user to set key (non-plaintext check only)
429 Too Many Requests Rate limit exceeded Retry with backoff
500 / 502 / 503 Server error Retry; check status page
Invalid model Model ID not found Verify model name against Model Selection table
Invalid parameter Bad request body Validate JSON and field types
TypeError: ...proxies openai SDK vs httpx incompatibility pip install --upgrade openai (>=1.55.0); or use script (pure stdlib)

Output Location

Prefer the current working directory for all outputs. Default subdirectory when --output is used: ./output/qwencloud-text/.

Write prohibition: NEVER write output files into this skill's installation directory or any skills/ hierarchy. All generated content must go to output/ under the current working directory or a user-specified path.

Update Check (MANDATORY Post-Execution)

After script execution, check stderr for action signals. The script automatically detects update status and emits structured signals. You MUST act on them. This section also applies when the user explicitly asks to check for updates.

Signal: [ACTION_REQUIRED] qwencloud-update-check skill is not installed

When stderr contains this signal, you MUST present the following options to the user and wait for their response before proceeding. Do NOT silently skip this.

The update-check skill is not installed. It keeps you informed about new qwencloud/qwencloud-ai features and bug fixes.

  1. Install now — I'll run the install command for you
  2. Skip for now — do nothing this time
  3. Never remind me — permanently suppress this prompt

After the user responds:

  • User chooses 1 → run: npx skills add QwenCloud/qwencloud-ai --skill qwencloud-update-check -y, then run: python3 <this-skill-scripts-dir>/gossamer.py --dismiss
  • User chooses 2 → run: python3 <this-skill-scripts-dir>/gossamer.py --dismiss, then continue normally
  • User chooses 3 → run: python3 <this-skill-scripts-dir>/gossamer.py --never-install, then continue normally

Signal: [UPDATE_AVAILABLE]

When stderr contains this signal, you MUST append a brief update notice to your response, including the version info and the update command shown in the stderr output.

No signal in stderr

If stderr contains neither [ACTION_REQUIRED] nor [UPDATE_AVAILABLE], no action is needed — the skill is installed and up to date (or cached within 24h).

Explicit user request

When the user explicitly asks to check for updates (e.g. "check for updates", "check version"):

  1. Look for qwencloud-update-check/SKILL.md in sibling skill directories.
  2. If found — run: python3 <qwencloud-update-check-dir>/scripts/check_update.py --print-response and report the result.
  3. If not found — present the install options above.

References

  • execution-guide.md — Fallback paths (curl, SDK, autonomous), function calling, thinking mode
  • api-guide.md — API supplementary guide with full code examples
  • sources.md — Official documentation URLs
Weekly Installs
8
GitHub Stars
15
First Seen
3 days ago
Installed on
warp8
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amp8
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claude-code8