Name: suppressing-noisy-errors
Rating: 76 (1 reviews)
Author: PostHog

suppressing-noisy-errors

Create PostHog error tracking suppression rules to drop high-volume, low-value errors at ingestion. Use when the user asks "stop capturing this error", "drop browser extension errors", "ignore ResizeObserver loops", "suppress bot-driven errors", or wants to reduce ingestion cost from noisy unactionable errors. Identifies suppression candidates, scopes the filter tightly, decides between full suppression and sampling, and confirms the rule before creating it. Suppressed errors are dropped permanently — this skill defaults to caution.

Quality

94%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a strong, executable playbook for a destructive operation: concrete payloads, a tight filter-scoping table, and validation/feedback checkpoints at every risky step. Conciseness and progressive disclosure are the only slightly trimmable dimensions.

Suggestions

Consider moving the HogQL execute-sql fallback and the noise-pattern filter table into a references/ file, keeping SKILL.md as the overview plus the core workflow — this would improve both conciseness and progressive_disclosure.

Tighten the 'When suppression is the right tool' / 'not the right tool' lists into a compact decision table to reduce prose while preserving the routing signal.

The 7-day dry-run estimate and the post-creation 24-48h watch window are time-sensitive; if these windows ever change, flag them so they don't silently stale-date the guidance.

Dimension	Reasoning	Score
Conciseness	Mostly efficient and free of basic-concept padding; the detail that is present (HogVM regex case-sensitivity, the coalesce ClickHouse wrapper, default overrides) is non-obvious domain knowledge that earns its place. A few prose passages (the 'right tool / not the right tool' framing) could be tightened slightly without losing signal.	4 / 5
Actionability	Provides copy-paste-ready API payloads for every step, a concrete filter-pattern table mapping noise types to exact filters, and a full executable HogQL fallback — specific examples cover the common cases.	5 / 5
Workflow Clarity	Seven clearly sequenced steps with explicit validation checkpoints: a dry-run in step 5, a flagged 'single most important safety check', mandatory user confirmation in step 6, and a post-creation watch loop in step 7 with a feedback path ('narrow the filter and rerun') for a destructive operation.	5 / 5
Progressive Disclosure	Well-organized into clear sections with no broken or buried file references and no bundle files to navigate; the single-file structure is appropriate for a workflow skill, though the inline filter-pattern table and HogQL fallback could optionally live in a reference file to slim the overview further.	4 / 5
	Total	18 / 20 Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is exemplary: concrete actions, explicit trigger phrases, both what and when clearly stated, and a distinct niche. It also signals the destructive/cautious default, which sharpens routing. No changes needed.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Create PostHog error tracking suppression rules to drop high-volume, low-value errors', 'Identifies suppression candidates, scopes the filter tightly, decides between full suppression and sampling, and confirms the rule before creating it' — covering the end-to-end task comprehensively.	5 / 5
Completeness	Explicitly answers both 'what' (create/identify/scope/decide/confirm suppression rules) and 'when' (a 'Use when the user asks...' clause with concrete trigger phrases), satisfying the top anchor exactly.	5 / 5
Trigger Term Quality	Quotes natural user phrases directly — 'stop capturing this error', 'drop browser extension errors', 'ignore ResizeObserver loops', 'suppress bot-driven errors' — plus the cost-reduction motivation, giving comprehensive coverage of terms users would actually say.	5 / 5
Distinctiveness Conflict Risk	Occupies a clear niche — dropping events at ingestion — with distinct triggers ('drop', 'suppress', 'stop capturing') that separate it from adjacent skills like grouping/archiving, keeping conflict risk minimal.	5 / 5
	Total	20 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: PostHog/posthog
Path: products/error_tracking/skills/suppressing-noisy-errors/SKILL.md
Commit: b0fece0

Reviewed: 4 days ago

Table of Contents

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