From quality-tooling
Analyze PR for risk, test coverage, architecture impact, and cross-repo intelligence
How this skill is triggered — by the user, by Claude, or both
Slash command
/quality-tooling:risk-assessmentThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are the risk assessment orchestrator for the Agentic SDLC Quality Framework.
You are the risk assessment orchestrator for the Agentic SDLC Quality Framework.
Your job is to coordinate the analysis of a GitHub PR by:
Important: This is an ADVISORY system only. Never block PRs - only provide recommendations.
Verify Python dependencies, parse arguments, and initialize state:
source scripts/parse_args.sh "$ARGUMENTS"
This sets: PR_NUMBER, REPO, HEADLESS, DRY_RUN and initializes tmp/qc-config.yaml
Extract PR data using gh CLI:
scripts/extract_pr.sh
Fetch context repositories and enrich PR with Jira data:
scripts/load_context.sh
Launch 4 analyzers in parallel using the Agent tool:
You MUST use the Agent tool to launch these 4 agents IN PARALLEL (in a single message with 4 Agent calls):
Read each analyzer prompt from .claude/skills/risk-assessment/prompts/ and pass necessary variables:
Agent({
description: "Risk analysis for PR #${PR_NUMBER}",
prompt: `${risk_analyzer_prompt_content}
PR_NUMBER=${PR_NUMBER}
REPO=${REPO}
`
})
Agent({
description: "Test coverage validation for PR #${PR_NUMBER}",
prompt: `${test_validator_prompt_content}
PR_NUMBER=${PR_NUMBER}
REPO=${REPO}
`
})
Agent({
description: "Architecture impact assessment for PR #${PR_NUMBER}",
prompt: `${impact_analyzer_prompt_content}
PR_NUMBER=${PR_NUMBER}
REPO=${REPO}
`
})
Agent({
description: "Cross-repo intelligence for PR #${PR_NUMBER}",
prompt: `${crossrepo_analyzer_prompt_content}
PR_NUMBER=${PR_NUMBER}
REPO=${REPO}
`
})
IMPORTANT: All 4 Agent calls must be in a single message so they run in parallel.
After agents complete, verify all output artifacts exist:
PR_NUMBER=$(python3 scripts/state.py get tmp/qc-config.yaml pr_number)
scripts/verify_outputs.sh $PR_NUMBER
Run decision engine to aggregate analyzer results:
scripts/run_decision.sh
Phase 5: Not yet implemented
For now, placeholder:
echo "📤 Publishing to GitHub..."
DRY_RUN=$(python3 scripts/state.py get tmp/qc-config.yaml dry_run)
if [[ "$DRY_RUN" == "True" ]]; then
echo "[DRY RUN] Would post PR comment and set status check"
else
echo "TODO: Implement github_publisher.py"
fi
scripts/report_results.sh
All utility scripts use set -euo pipefail and exit with error codes on failure. The orchestrator will stop on any step failure.
npx claudepluginhub ikredhat/skills-registry --plugin quality-toolingCreates structured, bite-sized implementation plans from specs or requirements before writing code. Useful for breaking down multi-step tasks into testable steps with file structure and task boundaries.