
X Bug Triage
FreeAutomate bug triage from X/Twitter complaints.
Free · Opens the source repo
What X Bug Triage does
X Bug Triage is a skill designed to streamline the process of detecting and managing bugs reported through public complaints on X (formerly Twitter). By automating the intake of complaints, this skill classifies and clusters them into relevant bug families, scans repositories for corroborating evidence, and efficiently routes issues to the appropriate owners. This is particularly useful for product teams who need to stay ahead of potential issues by monitoring social signals about their products.
The skill operates through a series of steps that begin with ingesting mentions from X, normalizing the data, and matching it against existing bug clusters. It utilizes a structured approach to classify and score the reliability of reports, ensuring that only the most relevant information is processed. This helps in creating a clear view of the product's health based on real-time feedback from users.
Once the bugs are triaged, the skill provides options for interactive review directly in the terminal, allowing users to take actions such as filing issues, merging reports, or escalating severity. The results can also be delivered to a Slack channel for team visibility, making collaboration on bug resolution more efficient. This skill is ideal for development teams looking to enhance their bug-tracking processes and respond rapidly to user-reported issues.
When to use it
Use this skill when you need to monitor product health through social media complaints and want to automate the triage process.
When not to use it
This skill may not be suitable for teams that do not use X/Twitter as a source for bug reports or those who prefer manual triage methods.
What you can build with it
Monitoring Product Health
Use this skill to keep track of user complaints on X/Twitter and proactively address bugs before they escalate.
Automating Bug Reports
Automate the process of triaging bugs reported on social media, reducing manual effort and increasing efficiency.
Collaborative Issue Management
Integrate results into your team's workflow by delivering summaries to Slack for collaborative review and action.
How to install X Bug Triage
View source1. Install with the skills CLI
npx skills add jeremylongshore/claude-code-plugins-plus-skills/x-bug-triage --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by jeremylongshoreX Bug Triage
Closed-loop bug triage from public X/Twitter complaints to clustered, evidence-backed GitHub issues.
Overview
Product teams learn about bugs from X/Twitter hours before internal monitoring catches them. This skill automates the pipeline: ingest complaints, classify and cluster them by bug family, scan repos for corroborating evidence, route to owners, and file issues — all with human confirmation gates. Results display directly in the terminal with optional Slack delivery for team review.
Prerequisites
- X API bearer token configured at
~/.claude/channels/x-triage/.env - SQLite database initialized (
bun run db:migrate) config/approved-accounts.jsonandconfig/approved-searches.jsonpopulated- GitHub CLI (
gh) for issue filing
Verify environment before starting:
!test -f data/triage.db && echo "DB ready" || echo "Run: bun run db:migrate"
!test -f config/approved-accounts.json && echo "Accounts configured" || echo "Missing: config/approved-accounts.json"
Instructions
Step 1: Intake
- Resolve account username to ID:
mcp__triage__resolve_username - Fetch mention timeline:
mcp__triage__fetch_mentions - Run approved searches:
mcp__triage__search_recent - Cross-reference mentions with search results for completeness
- Hydrate conversation threads for posts with conversation_id:
mcp__triage__fetch_conversation - Fetch quote tweets for high-engagement posts:
mcp__triage__fetch_quote_tweets
After intake completes:
- Call
assessFreshness()fromlib/freshness.tswith the combined post set and the requested window boundaries. Ifdate_confidenceis"low"or"medium", pass thewarningstring to the display step for rendering. - Collect all
DegradationReportobjects from intake tool responses. CallbuildSourceStatusReport()fromlib/source-status.tsto aggregate into aSourceStatusReport. Pass to the display step for rendering between the header and cluster list.
Step 2: Normalize
For each ingested post:
- Parse into BugCandidate (all 33 fields) using
lib/parser.ts - Classify into 12 categories using
lib/classifier.ts - Redact PII (6 types) using
lib/redactor.ts - Score reporter reliability (4 dimensions) using
lib/reporter-scorer.ts - Tag reporter_category from
config/approved-accounts.json
Step 3: Match Existing Clusters
- Load active clusters from DB
- Load active overrides and suppression rules
- For each candidate, compute bug signature and match against existing clusters at >=70% overlap
- Family-first guard: different families NEVER cluster
Step 4: Create/Update Clusters
- New matches: create cluster with initial severity "low"
- Existing matches: update report_count, last_seen, sub_status
- Resolved matches: set state to "open", sub_status to "regression_reopened"
- Suppressed candidates: skip with audit log
Step 5: Repo Scan
For each cluster (top 3 repos per cluster):
mcp__triage__search_issues— Match symptoms/errorsmcp__triage__inspect_recent_commits— 7-day commit windowmcp__triage__inspect_code_paths— Affected pathsmcp__triage__check_recent_deploys— Recent releases
Assign evidence tiers (1-4) per evidence-policy.md.
Load evidence tier definitions:
!cat ${CLAUDE_SKILL_DIR}/references/evidence-policy.md
Step 6: Route Ownership
For each cluster, use strict 6-level precedence:
mcp__triage__lookup_service_ownermcp__triage__lookup_oncallmcp__triage__parse_codeownersmcp__triage__lookup_recent_assigneesmcp__triage__lookup_recent_committers- Fallback mapping from config
Apply routing overrides from prior runs. Flag stale signals (>30 days).
Load routing precedence rules:
!cat ${CLAUDE_SKILL_DIR}/references/routing-rules.md
Step 7: Evaluate Severity + Escalation
Compute severity (low/medium/high/critical) based on:
- Report velocity, data loss signals, security/privacy, auth/billing lockout
- Cross-surface failure, enterprise impact, reproducibility quality
- Apply severity overrides from prior runs
Load escalation trigger definitions:
!cat ${CLAUDE_SKILL_DIR}/references/escalation-rules.md
Step 8: Display Results
Display triage results directly in the terminal as formatted markdown:
- Severity icons: red_circle critical/high, yellow_circle medium, green_circle low
- Top 5 clusters by severity (or all if <=5)
- Per cluster: report count, severity, status, assigned team, top evidence tier
- Available commands listed at the bottom
Step 9: Optional Slack Delivery
Check if claude-code-slack-channel plugin is available via mcp__slack__reply tool. If available, also deliver summary to Slack. If not, skip — terminal output is sufficient. Not an error.
Step 10: Interactive Review
Accept review commands from the user in the terminal. Parse via mcp__triage__parse_review_command.
| Command | Action |
|---|---|
details <#> | Display full cluster detail |
file <#> | Generate draft via mcp__triage__create_draft_issue |
dismiss <#> <reason> | Create noise_suppression override |
merge <#> <issue> | Link cluster to existing issue |
escalate <#> | Raise severity |
monitor <#> | Set cluster to monitoring |
snooze <#> <duration> | Temporarily suppress |
split <#> | Split cluster |
reroute <#> | Change routing |
full-report | Display all clusters |
confirm file <#> | File via mcp__triage__confirm_and_file |
After each command executes successfully, display the confirmation message from formatActionConfirmation() (in mcp/triage-server/lib.ts). This provides immediate user feedback for all review actions.
Load override and memory policy when processing review commands:
!cat ${CLAUDE_SKILL_DIR}/references/review-memory-policy.md
Step 11: Persist Learning
- All overrides stored in DB for future runs
- Audit log captures all actions (12 event types)
- Suppression rules created from dismiss commands
- Issue-family links created from file/merge commands
Output
Terminal markdown summary with severity-ranked clusters, evidence tiers, team assignments, and interactive command menu. Optionally mirrored to Slack.
Examples
/x-bug-triage @AnthropicAI --window 24h
Produces cluster summary, then user interacts:
> details 1
> file 2
> dismiss 3 noise
> confirm file 2
Error Handling
| Error | Cause | Solution |
|---|---|---|
| X_BEARER_TOKEN not set | Missing env config | Create ~/.claude/channels/x-triage/.env |
| Rate limited (429) | X API quota exhausted | Automatic retry with backoff, degrades gracefully |
| No clusters found | No bug-like posts in window | Widen --window or check approved-searches.json |
| Routing uncertain | No routing signals | Manual assignment required — flagged in output |
| Duplicate detected | Issue already filed | Use merge command instead of file |
Resources
References: ${CLAUDE_SKILL_DIR}/references/
- schemas.md — Data model reference (BugCandidate, BugCluster, 9 DB tables)
- routing-rules.md — 6-level routing precedence
- escalation-rules.md — 6 escalation triggers
- evidence-policy.md — 4-tier evidence hierarchy
- review-memory-policy.md — Override types and application order
Frequently asked questions about X Bug Triage
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