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Install Praxist runtime dependencies and configure user-level Praxist provider credentials for a source checkout or pip-installed environment.
Passed 15 of 20 test cases with the skill, and 3 of 20 without it.
and 19 more in the full report
14 fixed3 passed either way6 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
I want to set up Qwen as my LLM provider in Praxist. What environment variable name should be assigned to store my API key?
| Checked | Without skill | With skill |
|---|---|---|
| Maps the Qwen provider to the environment variable DASHSCOPE_API_KEY | Passed | Passed |
| Recommends using praxist setup --interactive for secret entry | Missed | Passed |
The instructions your model reads when the skill loads.
Use this skill to install dependencies needed to run Praxist itself. For local source checkouts, also install the repository's test/dev dependency group so the agent can validate Praxist code changes. Keep task-specific dependencies separate: each task project owns its own training/evaluation environment, datasets, CUDA/PyTorch stack, and benchmark packages.
This is separate from scripts/install_codex_skills.sh: that compatibility script installs or updates Codex or Claude Code skill symlinks. The bundled scripts/install_runtime_deps.sh in this skill installs Praxist runtime Python dependencies and, when explicitly supplied with provider/key options, writes user-level Praxist environment config.
Install dependencies for the Praxist control plane:
praxistagents,codexclaude-agent-sdk==0.2.136 plus MCP support for
agent_runtime:claude_sdk when a package or repaired install did not already
provide themopenai-codex==0.147.0, codex-relay==0.5.5, and MCP support for
agent_runtime:codex_sdk; this peer runtime uses the Python SDK and its local
app-server. The SDK-bundled Codex binary can own saved ChatGPT authentication
for native OpenAI, but Praxist does not reuse an interactive CLI processdependency-groups.devPRAXIST_LLM_PROVIDER, PRAXIST_AGENT_SYSTEM, and PRAXIST_MODEL only when the user supplies themstorage, only when the user asks for S3/object-storage supportcodex command is
present. The SDK-bundled binary is sufficient for Codex-native login, so do
not install a global CLI unless the user explicitly asksUse this install split:
docs
optional dependency group; do not invent a parallel requirements filetest cases passed, vs 3 / 20 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.