timeback-machine
v1.0.0Provides automated and manual rollback of long-running OpenClaw tasks by saving and restoring state snapshots to handle errors or unexpected issues.
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name, description, SKILL.md, and the included index.js align: the skill saves an in-memory snapshot (via configurable onSaveState), starts a timer, prompts the user, and restores via onRestoreState. There are no unrelated requirements (no network, no filesystem, no cloud creds).
Instruction Scope
SKILL.md and index.js limit actions to starting/stopping a timer, storing a snapshot in memory, prompting the user (via OpenClaw UI if available or confirm), and calling provided callbacks to save/restore state. The instructions do not reference arbitrary files, environment variables, or external endpoints.
Install Mechanism
Registry metadata shows no install spec (instruction-only), but SKILL.md contains an example 'npx clawhub install @Cortez_1/time-machine' snippet (the block in SKILL.md appears truncated). No downloadable archives or remote installers are used, so installation risk is low; verify how you obtain the package (official registry vs. third-party).
Credentials
The skill requests no environment variables, no credentials, and no config paths. Its functionality (in-memory snapshots and callbacks) does not require additional secrets or privileged access.
Persistence & Privilege
Flags show normal privileges (always: false, model invocation allowed). The skill does not persist data to disk or modify other skills' configurations; saved state is kept in-memory and cleared on cleanup.
Assessment
This skill appears to do exactly what it says: an in-memory rollback helper with a user-confirmation prompt. Before installing: (1) confirm you are obtaining the package from a trusted source/registry; (2) review or control the callbacks you pass as onSaveState/onRestoreState — those functions determine what gets captured/restored and could read or write sensitive data if implemented that way; (3) note the JSON-based deep-clone will not serialize functions, Dates, or non-JSON types — test with representative state; (4) the SKILL.md snippet is slightly malformed and package metadata contains minor author/name placeholders — treat as low-risk but review the package contents locally before running in production.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.