---

name: oasis description: "Use OASIS (camel-oasis) for LLM social-media simulations, agent profiles, platform actions, recommendation settings, SQLite traces, and legacy experiment analysis." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

OASIS Repo Skill

Use this skill for tasks involving OASIS / camel-oasis: agent-based Twitter-like or Reddit-like simulations, profile file preparation, AgentGraph and SocialAgent setup, ManualAction/LLMAction step orchestration, custom Platform and recommendation settings, OASIS SQLite trace databases, and legacy experiment analysis.

Start here

1. Confirm the package import and version with scripts/check_oasis_install.py.
2. Read references/api-overview.md for the public API surface and object relationships.
3. Route the task to the closest sub-skill below.
4. Use references/troubleshooting.md for install/import, credentials, optional backends, and DB lifecycle blockers.
5. Read references/repo-provenance.md before deciding whether this skill is stale for a different checkout or package version.

Install and import check

Normal package install:

pip install camel-oasis

Local checkout install:

pip install -e .

Minimal import check:

import oasis
print(oasis.__version__)
from oasis import AgentGraph, SocialAgent, UserInfo, ActionType, ManualAction

If import fails with FastMCP / mcp.server, use a compatible MCP version such as pip install 'mcp<2' or update CAMEL to a compatible release.

Sub-skill routes

Task	Read
Create or validate Reddit JSON/Twitter CSV profiles; build AgentGraph; customize SocialAgent, UserInfo, prompts, toolkits, or Neo4j graph backend.	sub-skills/agent-profiles/SKILL.md
Run or adapt Reddit/Twitter/custom simulations; manage env.reset() / env.step() / env.close(); use ManualAction and LLMAction; configure model backends and budgets.	sub-skills/simulation-workflows/SKILL.md
Choose ActionType and ManualAction.action_args; configure Platform, RecsysType, Clock, or Channel; inspect SQLite tables, traces, groups, reports, products, and recommendations.	sub-skills/platform-actions/SKILL.md
Triage legacy OASIS experiment YAMLs, generated-user flows, large-scale VLLM/OpenAI runs, score/counterfactual analysis, and visualization outputs.	sub-skills/experiments-analysis/SKILL.md

Safe default workflow

For a new task, prefer a tiny no-LLM path before provider-backed simulation:

1. Validate or create profiles with agent-profiles.
2. Run sub-skills/simulation-workflows/scripts/oasis_manual_smoke.py to prove local imports, SQLite, signup, post/comment/follow, and close behavior.
3. Inspect the generated database with sub-skills/platform-actions/scripts/oasis_db_summary.py.
4. Only then add real LLMAction, TwHIN/personalized recommendation, VLLM, OpenAI embeddings, Neo4j, or large experiment settings with explicit credentials and budget.

Important package facts

• Distribution name is camel-oasis; import name is oasis.
• The verified version for this skill is 0.2.5 on Python >=3.10,<3.12.
• ManualAction uses action_type and action_args. Some docs or snippets may show older action / args names; use the source-backed dataclass fields.
• actions passed to env.step() are keyed by SocialAgent objects, not integer agent IDs.
• Constructing SocialAgent(model=None) can require a non-empty OPENAI_API_KEY because CAMEL builds a default model backend. No real provider call occurs until an LLM-backed action is performed.
• The default Twitter platform uses twhin-bert recommendations, which may require optional model downloads or torch/CUDA resources. Use Reddit or random recommendation settings for tiny CPU-only checks.

Do not use this skill when

• The task is generic CAMEL agent framework development without OASIS social-platform objects.
• The task is only VLLM/Neo4j/OpenAI infrastructure setup and does not involve OASIS simulations.
• The user asks to perform downstream research interpretation without needing package operation guidance; then use the appropriate Researcher mode and loaded operating graph.

Router metadata

Structured router metadata lives in references/repo-routing-metadata.json. Do not hand-edit live routers; use the repo-skill verification/import protocol when importing is explicitly requested.