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negative-keywords

Mine and manage negative keywords from search-term reports to stop wasted spend, and detect match-type bleed and cross-campaign conflicts. Use when a user wants to cut wasted spend, clean up search terms, build negative lists, or fix irrelevant clicks on Google or Microsoft Ads.

Quality

94%

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SecuritybySnyk

Low

Low-risk findings worth noting

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 a crisp categorization taxonomy, and includes approval and post-change verification. The only soft spots are the unnamed 'plan tools' in the application step and the absence of a recovery loop when verification shows waste continuing.

Suggestions

Name the specific plan tools used to apply negatives in step 4, so the execution step is as concrete as the read steps.

Add one recovery instruction after the re-pull verification, e.g. what to do when a negated term's waste persists or a converting term was accidentally excluded.

Optionally specify where the search-term export should be requested from and in what format, since step 1 falls back to it when query-level detail is missing.

DimensionReasoningScore

Conciseness

About 30 lean lines with no explanations of concepts Claude already knows; every line carries operational weight ('Reads do not require approval; adding negatives is a change, so confirm before shipping').

5 / 5

Actionability

Names concrete tools (list_connected_accounts, research_campaign_opportunity, pull_google_ads_performance) and gives specific categorization and level-selection rules, but 'Apply negatives through the plan tools' leaves the actual application tooling unnamed. Not 3: guidance is concrete and executable apart from that gap.

4 / 5

Workflow Clarity

Clear 4-step sequence (read report, categorize, choose level, add on approval) with an approval checkpoint and a verification step ('Re-pull the search-term report after a few days to verify the waste stopped'). Not 5: no error-recovery loop telling Claude what to do if waste persists after negatives are applied.

4 / 5

Progressive Disclosure

Under 50 lines with well-organized numbered sections and no need for external references (no references/, scripts/, or assets/ bundle exists; the keyword-research mention is a cross-skill pointer, not a nested file reference), satisfying the simple-skill exception.

5 / 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 a model example: concrete third-person capabilities, an explicit 'Use when' clause with four natural trigger phrases, and platform qualifiers that sharpen distinctiveness. Every dimension lands on the top anchor without padding or over-claiming.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Mine and manage negative keywords from search-term reports', 'detect match-type bleed and cross-campaign conflicts' — in third person, comprehensively covering its niche (mine, manage, detect bleed, detect conflicts).

5 / 5

Completeness

Explicitly answers what ('Mine and manage negative keywords... detect match-type bleed and cross-campaign conflicts') and when ('Use when a user wants to cut wasted spend, clean up search terms, build negative lists, or fix irrelevant clicks').

5 / 5

Trigger Term Quality

Natural user phrasings like 'cut wasted spend', 'clean up search terms', 'build negative lists', and 'fix irrelevant clicks' plus platform names cover the space with synonyms ('negative keywords'/'negative lists', 'wasted spend'/'irrelevant clicks').

5 / 5

Distinctiveness Conflict Risk

Clear niche (negative keywords in search ads) with distinct triggers; minimal overlap risk even with adjacent skills like keyword research since the triggers center on negatives and wasted spend.

5 / 5

Total

20

/

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

skills/negative-keywords/SKILL.md

Reviewed

Table of Contents

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