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

User specified a model → use directly.
Consult the qwencloud-model-selector skill when model choice depends on requirement, scenario, or pricing.
No signal, clear task →
```
qwen3.5-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:

bash

python3 --version  # must be 3.9+

python3

is not found, try

python --version

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.

bash

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):

bash

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.

Install now — I'll run the install command for you

Skip for now — do nothing this time

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"):

Look for
```
qwencloud-update-check/SKILL.md
```
in sibling skill directories.

If found — run:

python3 <qwencloud-update-check-dir>/scripts/check_update.py --print-response

and report the result.

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

qwencloud-text

NPX Install

Tags

SKILL.md Content

Qwen Text Chat (OpenAI-Compatible)

Skill directory

Security

Key Compatibility

Model Selection

Execution

Prerequisites

Environment Check

Default: Run Script

Verify Result

On Failure

Quick Reference

Request Fields

Response Fields

Advanced Features

Error Handling

Output Location

Update Check (MANDATORY Post-Execution)

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

Signal:
`[UPDATE_AVAILABLE]`

No signal in stderr

Explicit user request

References