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Grouping Noisy Errors

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Consolidate duplicate error issues for cleaner tracking.

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What Grouping Noisy Errors does

Grouping Noisy Errors is a skill designed for developers using PostHog to manage error tracking more effectively. When the same error is reported multiple times under different fingerprints—often due to varying stack frames or dynamic data—this skill helps consolidate those reports into a single issue. This not only simplifies the error tracking process but also aids in identifying and resolving recurring issues more efficiently. The skill allows users to merge existing duplicate issues and establish durable grouping rules to prevent future occurrences of the same error from creating new fingerprints.

The process involves a two-step approach: first, users can identify candidate duplicate issues by querying the error tracking database. The skill provides tools to pull detailed information about each issue, allowing developers to confirm whether they are indeed duplicates based on specific criteria, such as the SDK used, exception type, and stack frames. Once duplicates are confirmed, users can merge them into a target issue, ensuring that all related events are attached to the correct report.

The second part of the skill focuses on creating grouping rules that rewrite the fingerprints of similar future events at ingestion time. This ensures that all matching future errors are categorized under a single canonical fingerprint, which helps maintain clarity and prevents the clutter of multiple similar issues. However, it's important to note that this skill is precise in its definition of what constitutes the same error; it does not merge errors from different SDKs, runtimes, or fundamentally different code paths, which preserves the integrity of error tracking and debugging.

This skill is particularly useful for teams that frequently encounter a high volume of similar error reports and need a systematic way to manage them. By consolidating these issues, developers can focus on resolving the underlying problems without being overwhelmed by noise in their error tracking system.

When to use it

Use this skill when you notice multiple reports of the same error type that appear to be duplicates, especially when dealing with noisy data from stack traces.

When not to use it

This skill is not suitable for grouping fundamentally different errors that arise from different SDKs, runtimes, or code paths, as it may obscure important debugging information.

What you can build with it

Cleaning Up Duplicate Reports

A developer notices multiple TypeError reports in PostHog and uses the skill to merge them into a single issue.

Establishing Grouping Rules

After merging duplicates, a team creates a grouping rule to ensure future occurrences of the same error are tracked under one fingerprint.

Managing Noisy Error Data

A project manager uses the skill to reduce clutter in error tracking, allowing the team to focus on resolving significant issues.

How to install Grouping Noisy Errors

View source

1. Install with the skills CLI

npx skills add posthog/posthog/grouping-noisy-errors --agent claude-code

2. 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 posthog

Grouping noisy errors

The same error can be reported as dozens of separate issues when stack frames or messages contain volatile data — random IDs, dynamic file paths, build hashes, anonymous function names. The fix is two-step: merge the existing issues into one target, then create a grouping rule so future events from the same call site share a single canonical fingerprint instead of spawning new ones.

Important up front: "same error" here is narrow. Two issues that share a name or a sentence of message text but came from different code paths, different SDKs, or different runtimes are different errors and should stay separate, even if the user thinks of them as "the same kind of bug". Grouping a frontend TypeError together with a backend TypeError because both messages contain "undefined" destroys the signal that lets the team find each one. The criteria in step 1 exist to keep that from happening.

Available tools

ToolPurpose
posthog:query-error-tracking-issues-listFind candidate duplicate issues
posthog:query-error-tracking-issuePull compact details for an individual issue
posthog:query-error-tracking-issue-eventsSampled $exception events with stack and message
posthog:error-tracking-issues-merge-createMerge existing issues into a target
posthog:error-tracking-issues-split-createSurgically split fingerprints back out if a merge errs
posthog:error-tracking-grouping-rules-createAuto-group future events into one issue
posthog:error-tracking-grouping-rules-listCheck existing grouping rules before adding new ones
posthog:error-tracking-issues-partial-updateRename or re-describe the target after a merge

Merge vs grouping rule

The two tools solve different halves of the problem:

  • Merge is one-shot. It collapses existing issues into a target and re-attaches their events. Future events still group by their original fingerprints — if the same noisy pattern keeps producing new fingerprints, merging is a treadmill.
  • Grouping rule is durable. It rewrites the fingerprint of any matching event to custom-rule:<rule_id> at ingestion time, so all future matches share one canonical fingerprint rather than spawning new ones. The first match either creates a new issue keyed off that fingerprint, or routes to whatever issue is already bound to it.

Use both together when the issue is recurring: merge historical duplicates into a target issue, then create the rule. The rule API does not accept a target issue ID — once the rule starts firing, the resulting custom-rule:... issue can be merged into the same target so the consolidation sticks. Use merge alone for historical sprawl that you don't expect to recur. Use a grouping rule alone for a brand-new pattern you're getting ahead of, when you don't need to consolidate with an existing issue.

Workflow

Step 1 — Confirm the duplicates

Search by exception type or message to find candidates:

posthog:query-error-tracking-issues-list
{
  "searchQuery": "TypeError: Cannot read property",
  "status": "active",
  "limit": 50,
  "orderBy": "occurrences",
  "dateRange": { "date_from": "-30d" }
}

For each candidate, pull one sampled exception event to compare stack, type, and message:

posthog:query-error-tracking-issue-events
{
  "issueId": "<candidate_issue_id>",
  "limit": 1,
  "include": ["exception", "stacktrace", "environment"]
}

Run this once per candidate. The tool defaults to onlyAppFrames: true, which makes the top in-app frame stand out at a glance. If two candidates share the same top frame and same exception type, they're likely the same error — but verify against the full checklist below before merging.

Are they the same error?

Treat two issues as duplicates only when every one of these matches:

  • $lib is the same SDK. The browser/JS SDK captures $lib as web (not posthog-js); server SDKs use posthog-python, posthog-node, etc. Confirm the exact value with read-data-schema (event_property_values for $lib on $exception) rather than assuming — a wrong value silently matches nothing. Errors from different SDKs almost always come from different code paths even when the exception type matches.
  • The exception type is identical ($exception_types).
  • The top in-app stack frame points at the same file and same function. Line numbers and minor offsets within that function are fine; a different file or a different function on top means a different bug.
  • The message follows the same template, with differences confined to volatile data — IDs, hashes, timestamps, dynamic paths. If the difference is a different verb, object, or operation, it's a different bug.
  • $exception_handled agrees (both handled or both unhandled). A caught variant and an uncaught variant are different code paths and benefit from staying separate.

If any single one of those differs, they are not duplicates — investigate separately (investigating-error-issue).

What NOT to group together

These are the failure modes that destroy debugging signal. Do not group across any of them, even when the user describes them as "the same kind of bug":

  • Frontend and backend variants of the same exception type. A TypeError from a browser bundle and a TypeError from a Node service share a name and often a message word, but the stack, the runtime, and the fix all differ.
  • Different SDKs / platforms. web (browser/JS) vs posthog-python vs posthog-node are different call sites.
  • Same type, different file or function on top of the stack. A NullPointerException thrown from OrderService.cancel is not the same bug as one thrown from PaymentService.refund, even if both messages say "user was null".
  • Caught vs uncaught. Two issues that differ only in $exception_handled are usually a code path that swallows the error in one place and lets it propagate in another — keeping them separate makes that visible.
  • Conceptually-similar bugs that happen to share a phrase. "Cannot read property of undefined" appears in many independent bugs. Without matching stack frames, message similarity alone is not enough.

Step 2 — Pick the target issue

Pick the issue that should absorb the others:

  • Most occurrences — keeps the dominant issue so dashboards stay continuous
  • Best name and description — if the user has annotated one, prefer it
  • Earliest first_seen — preserves the original timeline

Note the target's ID. The other candidates become ids to merge in.

Step 3 — Merge existing duplicates

posthog:error-tracking-issues-merge-create
{
  "id": "<target_issue_id>",
  "ids": ["<duplicate_id_1>", "<duplicate_id_2>", "..."]
}

Merge is destructive (annotation destructive: true) — once issues are merged into a target, the source issues are gone from the active list. Confirm the target with the user before calling. Cap each merge call at ~50 source IDs to keep failures localized; for larger sprawl, batch.

Merged changes may not appear in the issue list immediately — re-listing right after the call can still show the source issues for a short window. If a follow-up error-tracking-issues-list call looks unchanged, wait a few seconds and re-query rather than re-issuing the merge.

If after the merge the target's metadata looks wrong (a duplicate had a better name), use error-tracking-issues-partial-update to fix the name or description on the target rather than re-merging.

Step 4 — Decide if a grouping rule is warranted

A grouping rule is worth creating when both are true:

  • The pattern keeps producing new fingerprints (you have seen new duplicates appear since the last merge)
  • You can describe the pattern with property filters that won't accidentally swallow unrelated errors

The canonical exception properties ($exception_types, $exception_values for messages, $exception_sources for file paths, $exception_functions for function names) are arrays at capture time. PostHog's property filters special-case them — each filter matches against the individual array elements, so all the standard operators (exact, is_not, icontains, not_icontains, regex, not_regex) work with the bare value: exact "TypeError", not exact '["TypeError"]' or regex '"TypeError"'.

The singular forms ($exception_type, $exception_message) and $exception_stack_trace_raw are emitted on a fraction of a percent of events; filtering on them produces a rule that silently never matches.

If the volatility is in the message (e.g., TypeError at /static/main.<hash>.js), a regex filter on $exception_values works. If the volatility is in line numbers within a known file, icontains on $exception_sources does. $exception_handled is also a useful narrowing dimension — separate handled vs unhandled rather than mixing them.

Skip the grouping rule when:

  • The duplicates are historical (one-off backfill, no new occurrences) — merge is enough
  • You can't write a filter narrow enough to be safe — broaden the merge cadence instead and revisit later

Step 5 — Create the grouping rule

Translate the step 1 "same error" checklist into rule filters. A rule that matches more loosely than the checklist will silently merge unrelated bugs forever — the rule is more dangerous than the merge because it runs against every future event. At a minimum, scope by SDK and exception type, and add a third dimension (file path via $exception_sources, or a specific message phrase via $exception_values) to pin the call site.

Confirm the $lib value first — the browser/JS SDK captures $lib="web", not posthog-js, so a rule filtering on posthog-js silently never matches. Verify with read-data-schema (event_property_values for $lib on $exception) before baking a value into the rule:

posthog:error-tracking-grouping-rules-create
{
  "filters": {
    "type": "AND",
    "values": [
      {
        "type": "event",
        "key": "$lib",
        "operator": "exact",
        "value": "web"
      },
      {
        "type": "event",
        "key": "$exception_types",
        "operator": "exact",
        "value": "TypeError"
      },
      {
        "type": "event",
        "key": "$exception_sources",
        "operator": "icontains",
        "value": "/static/checkout/"
      },
      {
        "type": "event",
        "key": "$exception_values",
        "operator": "icontains",
        "value": "Cannot read property"
      }
    ]
  },
  "description": "Cleanup: collapse noisy checkout TypeError fingerprints (web)"
}

Rules are evaluated in order. List existing rules first (posthog:error-tracking-grouping-rules-list) — if a rule already partially covers the pattern, prefer adjusting its filter over stacking a near-duplicate.

The optional assignee field auto-assigns issues created by the rule. Skip it unless the user explicitly wants ownership baked into the rule.

Step 6 — Verify and consolidate

Sample the merged issue's recent events to confirm the merge succeeded. Watch for the rule's custom-rule:<rule_id> fingerprint to start matching events — the first match creates a new issue (or routes to whatever was already bound to that fingerprint). To keep events under your historical target rather than scattered across the new custom-rule issue, run a second merge folding the custom-rule issue into the target.

If new (non-rule) fingerprints continue appearing despite the rule, its filter is too narrow — widen it.

Tips

  • The user often confuses grouping rules with assignment rules. Grouping rules decide which issue an event lands in. Assignment rules decide who owns the resulting issue.
  • Don't merge issues that "look similar" without inspecting events. Two TypeErrors in different files are different bugs.
  • Stack frames are the canonical grouping signal — ingestion already fingerprints on the stack, so a stable stack groups itself. A grouping rule is for cases where the natural fingerprint sprays (volatile filenames, hashed function names, dynamic line numbers) and you need to override it.
  • Disabling or tightening a grouping rule does not retroactively un-group existing events; future events route correctly, past events stay where they are. Use error-tracking-issues-split-create if you need to surgically separate fingerprints back out of a merged issue.
  • Grouping rules are visible in the UI under Project settings → Error tracking → Grouping rules; mention this when the user asks where rules live.

Frequently asked questions about Grouping Noisy Errors

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