replay — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited replay (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Replay is an inspection over frozen state. It does not execute new experiments and must not modify live graph nodes, ratings, judgments, or preregistrations.
mcp__memory__list_snapshots(limit=20). Show label, timestamp, and counts; do not create a new snapshot merely to replay the past.
Approve hyp_07 instead of pausing it.
mcp__memory__replay_counterfactual(snapshot_id, counterfactual) andretain the returned branch_id.
scripts, seed_perturb, or the sequestered-data query tool.
user may later call resume_branch; replay itself never flips status.
Return:
snapshot_id: <snap_...>
branch_id: <replay_...>
counterfactual: <one sentence>
live_graph_mutated: false
evidence: <recorded facts used>
finding: <what changes under the counterfactual>
recommendation: <none or explicit user action>
limitations: <what replay cannot establish without a new experiment>For several what-ifs, create one replay branch per counterfactual and keep each output independent. Use mcp__memory__list_replay_branches(limit=20) to audit existing branches before adding duplicates.
Replay is complete when the source snapshot and new branch are identifiable, the live graph is unchanged, every finding cites recorded snapshot evidence, and any proposed live change is clearly left for separate user approval.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.