AI-generated analysisPublished automatically and not human-verified. Validated context appears in community notes below.
← Watch feed
Informational 15 Bitcoin

build: add PR severity classification workflow

Public commit record

What the developer wrote

Authored by Olaoluwa Osuntokun

90/100 · Strong
build: add PR severity classification workflow

Add a GitHub Actions workflow that uses Claude Code to automatically
classify PRs by severity based on the files changed. This helps
reviewers prioritize and understand PR complexity at a glance.

The workflow:
- Triggers on PR open and synchronize events
- Uses Claude Code to analyze changed files against severity mapping
- Applies one of four severity labels (critical/high/medium/low)
- Posts a detailed comment explaining the classification
- Supports manual override via severity-override-* labels

Severity mapping:
- CRITICAL: lnwallet, htlcswitch, contractcourt, peer, keychain, input,
channeldb, funding, lnwire, server.go, rpcserver.go
- HIGH: routing, invoices, sweep, discovery, graph, watchtower, feature,
lnrpc, macaroons, chainntnfs, etc.
- MEDIUM: payments, autopilot, lncfg, kvdb, proto files, etc.
- LOW: docs, tests, scripts, CI/CD config
✓ Descriptive subject✓ Names a concrete action or component✓ Uses a recognizable type or scope✓ Provides detailed explanatory context✓ Mentions testing or verification
The short version

What changed, and why it matters

This commit adds a new GitHub Actions workflow that automatically labels pull requests by severity based on which files they change. It is purely a repository automation/CI change and does not modify any of the actual Lightning node code that handles money, networking, or cryptography. There is no security vulnerability in this commit.

Recommended action

No security action required. As a routine hardening suggestion, ensure the CLAUDE_CODE_OAUTH_TOKEN and PR_SEVERITY_BOT_TOKEN secrets are scoped only to this workflow's required permissions, and periodically review labels/comments posted by the bot for prompt-injection or misclassification issues.

Security signals we found

No strong security signals were identified.

Risk score

Why this scored 15/100

Our methodology →
Potential impact 0/30
Exploitability 0/25
Stealth signal 0/15
Affected reach 0/15
Confidence 10/10
Evidence quality 5/5
Human-validated context

Community notes

Notes can correct, qualify, or add evidence to the AI analysis. Every note shown here has been validated by a human moderator.

No validated notes yet.

The AI analysis stands alone for now. Submit a note if you can add evidence or important context.