Praxist Interactive Task Init
Build a Praxist task project through a confirmation-first interactive agent workflow.
Install
npx skills add sapientinc/PRAXIST --skill praxist-interactive-task-init -g -a claude-code -y- Repository
- sapientinc/PRAXIST5.5k
- Category
- AI and agents
- Updated
- 1mo ago
- License
- See repository
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
Build a Praxist task project through a confirmation-first interactive agent workflow. Use when a user wants Praxist task initialization with human confirmation of research goals, constraints, metrics, ranking rules, evaluation protocol, compute budget, baseline handling, or launch readiness; when the user asks for an interactive task init skill; or when the agent should propose a task harness first and ask the user to approve or revise it before writing files.
Praxist Interactive Task Init
Use this skill when task initialization needs explicit user confirmation. It is
a thin interactive layer over praxist-task-initialization, not a separate
task format.
This layer inherits the complete current runtime contract from
praxist-task-initialization. Keep agent_runtime:claude_sdk as the default
unless the user approves another runtime. If the user selects
agent_runtime:codex_sdk, apply the SDK/MCP/relay readiness and task-boundary
rules from that skill; do not treat the interactive agent CLI hosting this
conversation as the peer runtime. Its saved ChatGPT authentication may be
approved for native OpenAI, but must remain operator-owned and outside the
generated task. Preserve the tested runtime pins inherited from task
initialization: claude-agent-sdk==0.2.136, openai-codex==0.147.0, and
codex-relay==0.5.5.
Provider-specific context efficiency is runtime-owned. When the user selects Codex-native mode or OpenRouter, explain that Praxist automatically coalesces finding-only continuation wakeups without deleting or compressing canonical evidence. Do not offer task-local cache, memory-store, or session-batching fields. Direct DeepSeek runs preserve their existing behavior.
Reasoning effort is inherited from the complete task-init contract. Propose
agent.reasoning_effort: max; ask for confirmation only when the user raised
reasoning depth, latency, or cost as a constraint, and preserve any explicit
off, low, high, or max answer.
Interaction Principle
Use confirmation first, not input first:
- Inspect the project and propose a concrete harness decision.
- Ask the user whether to accept or correct it.
- Apply accepted decisions to the normal task-initialization workflow.
