scenique-context-frame

Detects topic switches in conversations and creates or manages Context Frames to maintain work-related context.

Security Scan

The skill's code mostly matches its stated purpose, but it silently writes to a hard-coded root workspace path (/root/.openclaw/workspace/context_frames_pending.json) that is not documented in SKILL.md and is unexpected for a lightweight demo, so review is recommended before installing.

Purpose & Capability

The name/description (detect topic switches and manage Context Frames) aligns with the code (context_sim.py implements simple heuristics and frame management). However, the skill writes a JSON file to a hard-coded path under /root/.openclaw/workspace/context_frames_pending.json when switching frames — this filesystem interaction was not documented in SKILL.md nor declared in required config paths and appears disproportionate for a demo/instruction-only skill.

Instruction Scope

SKILL.md instructs running preload.py (and mentions a demo simulate mode) and does not disclose any filesystem side effects. The runtime code, however, attempts to read/append/write a JSON file at /root/.openclaw/workspace/context_frames_pending.json inside a try/except block. This is an undocumented I/O action that the agent will perform if the code runs and the environment permits it.

Install Mechanism

No install spec or remote downloads are present; the skill is delivered as local Python files (preload.py and context_sim.py) and runs locally. There are no external package pulls or network-based installers in the manifest.

Credentials

The skill declares no required environment variables or credentials, which is consistent with the contained code (no network calls or secrets use). However, the hard-coded filesystem path under /root implies it expects access to a specific workspace location; that expectation should be documented or made configurable rather than baked in.

Persistence & Privilege

The skill is not marked always:true and does not modify other skills' configuration. Its only persistence is the local write to a workspace file under /root/.openclaw, which is limited in scope but should be treated cautiously because it's not documented.

What to consider before installing

This skill appears to do what it says (naive topic-switch detection and context-frame management) and does not perform network calls or require credentials, but it writes an undocumented file to /root/.openclaw/workspace/context_frames_pending.json. Before installing or running it in a production agent, ask the maintainer to: (1) explain and document why the skill writes to that path, (2) make the path configurable (e.g., via an env var or agent-provided workspace API), or (3) change it to a clearly scoped, non-root workspace location. Run the skill in a sandbox first, inspect the created JSON, and ensure file permissions and ownership are appropriate. If you cannot get those assurances, avoid installing it on systems where writing to /root or an agent workspace is sensitive.

Context Frame Skill

Purpose

• Detect topic switches in conversation and create/manage Context Frames (work contexts).

Usage

• context_simulate: demo mode runs a simulated conversation and shows frame creation.

Integration

• Designed to be integrated into Consolidator or called as an isolated skill for on-demand context management.

Notes

• MVP uses lightweight heuristic topic detection; can be upgraded to embedding-based semantic similarity for production.

Packaging

• Files included: context_sim.py, preload.py, skill.json, SKILL.md
• To test locally: python3 preload.py
• To publish: upload the packaged tarball via ClawHub upload UI or use npx clawhub publish <path> (web upload recommended for first-time publish to accept license).