Skills osop-review
Review .osop/.osoplog for security risks, permission gaps, and destructive commands
install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/archie0125/osop-review" ~/.claude/skills/clawdbot-skills-osop-review && rm -rf "$T"
manifest:
skills/archie0125/osop-review/SKILL.mdsource content
OSOP Workflow Reviewer
Review a workflow or execution log for risks and issues.
Target file
$ARGUMENTS
What to do
-
Read the file specified in the argument (
or.osop
).osoplog.yaml -
Analyze for risks — check each node for:
without precedingsecurity.risk_level: high|criticalapproval_gate
containing broad patterns (security.permissions
,write:*
,admin:*
)delete:*
nodes with destructive commands (cli
,rm -rf
,kubectl delete
,terraform destroy
)DROP TABLE- Hardcoded secrets (strings starting with
,sk-
,ghp_
, API keys)xoxb- - Agent nodes without
(unbounded cost exposure)cost.estimated - Missing
on external call nodes (timeout_sec
,api
,cli
,agent
,infra
)mcp - Missing error handling (no
/fallback
edge) on medium+ risk nodeserror
-
Compute risk score (0-100):
- Each node:
type_weight * risk_multiplier * mitigation_factor - Type weights: cli=2, infra=2, db=1.5, agent=1.5, docker=1.5, cicd=1.5, api=1, others=0.5-1
- Risk multiplier: low=1, medium=2, high=4, critical=8
- Mitigations: approval_gate=-50%, retry_policy=-10%, fallback_edge=-20%
- Finding penalty: low=+2, medium=+5, high=+10, critical=+20
- Each node:
-
Present findings in a clear table:
Risk Score: XX/100 — VERDICT (safe/caution/warning/danger) | Severity | Finding | Node | Suggestion | |----------|---------|------|------------| | CRITICAL | ... | ... | ... | -
Summarize:
- Total permissions required
- Secrets referenced
- Estimated cost (if any)
- Whether approval gates exist
- Final verdict: is this safe to run?
For .osoplog files
If reviewing an execution log, also check:
- Which tools were actually used and how many calls
- Whether any nodes failed and why
- AI reasoning decisions — were they sound?
- Sub-agent hierarchy — was the spawning appropriate?
- Total execution time and cost