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anomaly-detector

Catch spend spikes, CTR or conversion-rate drops, budget runaway, and metric outliers across campaigns, and set sane alert thresholds. Use when a user asks why spend or performance changed suddenly, wants monitoring or alerts, or something looks off in the numbers.

Quality

89%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is anomaly-detector in Synter-Media-AI/plugin

SKILL.md
Quality
Evals
Security

Quality

Content

86%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.

A tight, well-sequenced instruction-only skill: it names the exact tools to call, gives domain-specific diagnostic heuristics instead of generic advice, and gates destructive actions behind approval and diagnosis. The main gaps are underspecified threshold guidance ('sane alert thresholds' with no window or deviation rule) and no post-action verification loop.

Suggestions

Define what makes an alert threshold 'sane' — e.g., 'flag when daily spend exceeds 1.5x the trailing 7-day average for 2 consecutive days' — so threshold recommendations are deterministic rather than judgment calls.

Specify a default baseline window for step 1 (e.g., 'pull the trailing 30 days plus today') so the historical comparison is reproducible.

Add a post-action check after thresholds are configured or a campaign is paused (e.g., re-review metrics after 24–48 hours to confirm the fix landed), completing the feedback loop.

DimensionReasoningScore

Conciseness

The body is lean and assumes competence: "Find the sudden change before it burns a budget" followed immediately by tool calls (`pull_google_ads_performance`, `pull_meta_ads_performance`, ...) and domain-specific heuristics like "a tracking outage reads as a conversion cliff; a new campaign launch reads as a spend spike; a weekend reads as a volume drop". No padding or explanation of concepts Claude already knows, matching the 5 anchor 'Lean and efficient; assumes Claude's competence; every token earns its place'.

5 / 5

Actionability

Concrete tool names are given (`list_connected_accounts`, five `pull_*_ads_performance` variants) and the action section is specific ("Recommend alert thresholds... Do not claim alerts were installed", "pause, budget cut, creative swap", route to **pre-pause-analysis**). It sits at 'Mostly executable guidance; concrete code or commands with minor gaps' because the threshold logic is underspecified — "set sane alert thresholds" never defines what a sane threshold is (window, deviation multiple), and the baseline window to pull is left open.

4 / 5

Workflow Clarity

The numbered sequence (baseline → outliers → diagnose → act) is clear with explicit checkpoints: "State the period and missing data before calling a change abnormal", "Confirm the cause before recommending action", and the approval gate "setting alerts or pausing is a change and waits for approval". This matches 'Clear sequence with most checkpoints present; minor validation gaps' — validation before acting is present (so the destructive/batch cap does not apply), but there is no post-action re-check loop (e.g., verifying thresholds fire correctly after configuration), keeping it below the 5 anchor.

4 / 5

Progressive Disclosure

The skill is under 50 lines with no bundle files and no need for external references; per the rubric's simple-skill guideline, well-organized sections alone warrant a 5. Sections are clearly headed (numbered workflow steps plus a Rules section), and the single cross-reference to **pre-pause-analysis** is clearly signaled rather than buried.

5 / 5

Total

18

/

20

Passed

Description

88%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.

A strong description that explicitly states concrete capabilities (four anomaly types plus threshold setting) and an explicit, naturally-phrased 'Use when' trigger clause. The only weaknesses are a few missing common synonyms (overspend, pacing, ROAS, CPA/CPM) and slightly generic trigger phrasing ('monitoring or alerts', 'looks off in the numbers') that creates minor overlap risk with non-ad monitoring skills.

DimensionReasoningScore

Specificity

The description lists multiple concrete, domain-specific actions: "Catch spend spikes, CTR or conversion-rate drops, budget runaway, and metric outliers across campaigns, and set sane alert thresholds" — four named anomaly types plus threshold setting. This matches the anchor 'Lists multiple specific concrete actions; comprehensive coverage' (compare the 5-anchor PDF example with 4 actions); it is above the 4 anchor because coverage of the ad-anomaly domain is complete rather than having minor gaps.

5 / 5

Completeness

Both parts are explicit: the what is "Catch spend spikes, CTR or conversion-rate drops, budget runaway, and metric outliers across campaigns, and set sane alert thresholds", and the when is "Use when a user asks why spend or performance changed suddenly, wants monitoring or alerts, or something looks off in the numbers". This directly matches the 5 anchor 'Clearly and explicitly answers both what AND when with concrete trigger phrases'; the 4 anchor would require a less explicit when-clause.

5 / 5

Trigger Term Quality

Natural user phrasing is present: "why spend or performance changed suddenly", "wants monitoring or alerts", "something looks off in the numbers", plus terms like spend spikes, CTR, conversion-rate drops, budget runaway. This fits 'Good keyword coverage; a few natural terms missing' — common synonyms such as overspend/overspending, pacing, ROAS, or CPA/CPM (which the skill body actually covers) are absent, keeping it below the comprehensive 5 anchor.

4 / 5

Distinctiveness Conflict Risk

The ad-campaign anomaly niche is clear and mostly distinct, but the trigger phrases "wants monitoring or alerts" and "something looks off in the numbers" are not domain-qualified and could overlap with generic monitoring or non-ad reporting skills. This fits 'Mostly distinct; minor overlap risk with closely related skills' rather than the 5 anchor's 'minimal conflict risk'.

4 / 5

Total

18

/

20

Passed

Validation

100%

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

Synter-Media-AI/plugin

Path

packages/claude-directory/skills/anomaly-detector/SKILL.md

Reviewed

Table of Contents

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