Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
cascadeflow: Cost + Latency Reduction
OpenClaw-native domain cascading. Use when users need cost/latency reduction via cascading, domain-aware model assignment, OpenClaw-native event handling, an...
skill openclawclawhub Free
OpenClaw-native domain cascading. Use when users need cost/latency reduction via cascading, domain-aware model assignment, OpenClaw-native event handling, an...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, agents/openai.yaml, references/clawhub_publish_pack.md, references/market_positioning.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.1.1
Provenance
- Publisher
- saschabuehrle
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
CascadeFlow: Cost + Latency Reduction | 17+ Domain-Aware Models + OpenClaw-Native Events
Use CascadeFlow as an OpenClaw provider to lower cost and latency via cascading. Assign up to 17 domain-specific models (for coding, web search, reasoning, and more), including OpenClaw-native event handling, and cascade between them (small model first, verifier when needed). Keep setup minimal, then verify with one health check and one chat call.
Why Use It
Reduce spend with drafter/verifier cascading. Run 17+ domain-aware model assignments (code, reasoning, web-search, and more). Support cascading with streaming and multi-step agent loops. Handle OpenClaw-native event/domain signals for smarter model selection.
Security Defaults
Install from PyPI and verify package artifact before first run. Keep the server bound to localhost by default. Use explicit auth tokens for chat and stats endpoints (recommended for production). Expose remote access only behind TLS/reverse proxy with strong tokens. Use least-privilege provider keys (separate test keys from production keys).
How It Works
OpenClaw sends requests to CascadeFlow through OpenAI-compatible /v1/chat/completions. CascadeFlow reads prompt context plus OpenClaw-native event/domain metadata (for example metadata.method, metadata.event, and channel/category hints). CascadeFlow selects a domain-aware drafter/verifier pair (small model first). If quality passes threshold, drafter answer is returned (cost/latency advantage). If quality fails threshold, verifier runs and final answer is upgraded. The same cascading behavior is supported for streaming and multi-step agent loops.
Advantages
Lower average cost by avoiding verifier calls when not needed. Lower average latency for simple and medium tasks. Better quality on hard tasks through verifier fallback. Better operational handling through OpenClaw-native event/domain understanding.
Quick Start
Or ask your OpenClaw agent to set it up for you as an OpenClaw custom provider with OpenClaw-native events and domain understanding. Install and verify package source: python3 -m venv .venv source .venv/bin/activate python -m pip install --upgrade "cascadeflow[openclaw]>=0.7,<0.8" python -m pip show cascadeflow python -m pip download --no-deps "cascadeflow[openclaw]>=0.7,<0.8" -d /tmp/cascadeflow_pkg python -m pip hash /tmp/cascadeflow_pkg/cascadeflow-*.whl Optional variants: python -m pip install --upgrade "cascadeflow[openclaw,anthropic]>=0.7,<0.8" # Anthropic-only preset python -m pip install --upgrade "cascadeflow[openclaw,openai]>=0.7,<0.8" # OpenAI-only preset python -m pip install --upgrade "cascadeflow[openclaw,providers]>=0.7,<0.8" # Mixed preset Pick preset + credentials: Presets: examples/configs/anthropic-only.yaml, examples/configs/openai-only.yaml, examples/configs/mixed-anthropic-openai.yaml Provider key(s): ANTHROPIC_API_KEY=... and/or OPENAI_API_KEY=... (required based on selected preset) Service tokens: --auth-token ... and --stats-auth-token ... (recommended for production; use long random values) Start server (safe local default): set -a; source .env; set +a python3 -m cascadeflow.integrations.openclaw.openai_server \ --host 127.0.0.1 --port 8084 \ --config examples/configs/anthropic-only.yaml \ --auth-token local-openclaw-token \ --stats-auth-token local-stats-token Optional harness activation (runtime in-loop policy controls): # Observe first (recommended): log decisions, no blocking python3 -m cascadeflow.integrations.openclaw.openai_server \ --host 127.0.0.1 --port 8084 \ --config examples/configs/anthropic-only.yaml \ --harness-mode observe # Enforce mode with limits python3 -m cascadeflow.integrations.openclaw.openai_server \ --host 127.0.0.1 --port 8084 \ --config examples/configs/anthropic-only.yaml \ --harness-mode enforce \ --harness-budget 1.0 \ --harness-max-tool-calls 12 \ --harness-max-latency-ms 3500 \ --harness-compliance strict Configure OpenClaw provider: baseUrl: http://<cascadeflow-host>:8084/v1 (local default: http://127.0.0.1:8084/v1) If remote: http://<server-ip>:8084/v1 or https://<domain>/v1 (TLS/reverse proxy) api: openai-completions model: cascadeflow apiKey: same value as your --auth-token
Commands
/model cflow: default OpenClaw model switch using alias cflow. /cascade: optional custom command (if configured in OpenClaw). /cascade savings: optional custom subcommand for cost stats. /cascade health: optional custom subcommand for service status.
Links
Full setup + configs: references/clawhub_publish_pack.md Listing strategy: references/market_positioning.md Official docs: https://github.com/lemony-ai/cascadeflow/blob/main/docs/guides/openclaw_provider.md GitHub repository: https://github.com/lemony-ai/cascadeflow
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs1 Config
- SKILL.md
- references/clawhub_publish_pack.md
- references/market_positioning.md
- agents/openai.yaml