Risha.ai Content Generation
/install risha-content-generation
Risha Content Generator
Use this skill to drive Risha's capability workflow from discovery through final output retrieval. Prefer the bundled helper script for repeated API work so the request flow stays consistent and the payload shape remains inspectable.
Workflow
- Gather credentials and decide the auth mode.
- Load the bundled capability catalog or refresh it from the live account.
- Inspect the chosen capability's manual fields to build valid
prompt_data. - Optionally inspect creator choices for creator-backed text workflows.
- Estimate credits before submitting.
- Submit a generation request and poll until it finishes.
- Return the final generated content or explain the failure clearly.
Choose Auth Mode
Prefer one of these auth approaches:
RISHA_AUTH_HEADERwhen the caller already has a working header such asBearer ...orBasic ....RISHA_EMAILandRISHA_PASSWORDwhen the skill can log in directly through/api/auth/login/.
Set RISHA_API_BASE_URL only if the host changes. The default is https://adminxcore-api.risha.ai/api.
Before doing generation work, validate auth with the helper:
python3 scripts/risha_api.py me
If login succeeds but the script cannot derive a reusable auth token/header from the response, stop guessing and ask the user for the exact header format that works in their environment.
Load The Capability Catalog First
Never hardcode prompt_data blindly. The valid keys come from each capability's linked manual definition.
This skill now ships with a current account snapshot:
Refresh that snapshot in one step when needed:
python3 scripts/risha_api.py catalog \
--quiet \
--write-json references/current-capabilities.json \
--write-markdown references/current-capabilities.md
Use the catalog for:
- capability IDs
- category and output type
- async vs sync behavior
- required inputs
- field choice sources
- current input and output schemas
When you need one capability in full detail, inspect it directly:
python3 scripts/risha_api.py capability 123
Use the capability manual to inspect:
manual.fields- each field's
field_path json_typeis_requiredchoice_modelenum_values- credit rules when present
Build prompt_data from those manual fields. Use the field path exactly as Risha expects. For nested paths such as input.text, create nested JSON objects.
The current account snapshot includes 17 accessible capabilities across:
multimodaltext_generationtts
Treat the snapshot as the fast path and the live catalog command as the refresh path.
Inspect Creator Choices When Needed
For creator-backed writing flows, inspect available creators before choosing one:
python3 scripts/risha_api.py creators
If the relevant manual field uses choice_model: creators, pass the creator's field_value, not just its label.
Use the same pattern for dialects and voices when the manual points to those choice models.
Generate Content
The helper now includes credit preview by default. Before every generate request, it fetches:
- current available credits
- estimated cost for the selected capability and
prompt_data - projected remaining credits after submission
If you want the preview without creating anything, use:
python3 scripts/risha_api.py estimate \
--capability-id 123 \
--prompt-data-file /absolute/path/prompt-data.json
Pass either inline JSON or a JSON file:
python3 scripts/risha_api.py generate \
--capability-id 123 \
--title "LinkedIn post draft" \
--prompt-data '{"input":{"topic":"AI adoption","tone":"confident"}}'
Or:
python3 scripts/risha_api.py generate \
--capability-id 123 \
--prompt-data-file /absolute/path/prompt-data.json \
--wait
Use --wait to poll until the request reaches a terminal state. Terminal states are:
completedfailedcancelled
When completed, prefer returning:
generated_content.contentfor textgenerated_content.assetorthumbnailURLs for mediagenerated_content.content_metadatawhen it contains useful structured extras
The generate response now includes a credit_preview block alongside the request or final generation result.
Chat Endpoint
Risha also exposes /api/chat/ and /api/chat/stream/, but the schema does not currently describe their request bodies. Treat those endpoints as exploratory only unless the user provides working payload examples. Prefer the capability plus generation-request flow for reliable automation.
Troubleshooting
- If
/auth/login/returns400withInvalid email or password, confirm credentials before retrying. - If a generation request fails, inspect
error_messageon the request record. - If a capability detail lacks enough manual information, read references/risha-api.md and inspect the live capability JSON with the helper before constructing payloads.
- If the API host returns intermittent
502 Bad Gateway, retry with backoff instead of rewriting the workflow.
Resources
- Use scripts/risha_api.py for authenticated API calls, capability inspection, catalog refresh, and generation polling.
- Use references/risha-api.md for the endpoint map, auth notes, and payload-building rules derived from the published schema at
https://adminxcore-api.risha.ai/api/docs/?format=openapi. - Use references/current-capabilities.md as the ready-to-browse capability inventory.
- Use references/current-capabilities.json when exact field names and schemas are needed without another API round-trip.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install risha-content-generation - 安装完成后,直接呼叫该 Skill 的名称或使用
/risha-content-generation触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Risha.ai Content Generation 是什么?
Discover, prepare, and execute any Risha.ai capability available to the authenticated account. Use when Codex needs to authenticate to a Risha workspace, loa... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 36 次。
如何安装 Risha.ai Content Generation?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install risha-content-generation」即可一键安装,无需额外配置。
Risha.ai Content Generation 是免费的吗?
是的,Risha.ai Content Generation 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Risha.ai Content Generation 支持哪些平台?
Risha.ai Content Generation 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Risha.ai Content Generation?
由 aimedialab(@aimedialab)开发并维护,当前版本 v1.0.0。