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ad-campaign-analyzer

Analyze cross-channel campaign data, quantify uncertainty, and propose evidence-labeled budget tests without overstating causality.

Quality

70%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

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tessl review fix ./plugins/agentic-awesome-skills-claude/skills/ad-campaign-analyzer/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

70%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 rigorous, well-sequenced analysis workflow with strong statistical hygiene, explicit validation checkpoints, rollback rules, and a complete output template — the workflow clarity is exemplary for an instruction-only skill. The main costs are length (a duplicated trigger list and a ~100-line inline report template) and the absence of any progressive disclosure: the output format and platform tables belong in reference files.

Suggestions

Remove or merge the 'Examples' section (lines 373–382), which nearly duplicates the 'When to Use This Skill' list (lines 27–36) — keep one trigger list.

Move the Phase 5 output template and the per-platform expected-columns tables into references/ files (e.g. OUTPUT_TEMPLATE.md, PLATFORM_FORMATS.md) linked from a short summary, cutting SKILL.md roughly in half.

Add a short executable snippet or named tool invocation for the statistical significance and sample-size calculations so the A/B guidance is copy-paste ready rather than directive-only.

DimensionReasoningScore

Conciseness

The body is dense with domain-specific guidance and never explains concepts Claude already knows, but the ~100-line Phase 5 output template and placeholder-heavy tables inflate length, and the 'Examples' section duplicates the 'When to Use This Skill' trigger list almost verbatim — matching 'mostly efficient but could be tightened'.

3 / 5

Actionability

Concrete, executable guidance throughout: per-platform expected columns, the CAC formula, a pre-registered statistical-test spec (alpha, power, MDE, stopping rule), rollback criteria, a full report template, and an exact output filename convention. Minor gaps remain — e.g. the statistical calculations are directed ('use a justified bootstrap or model') without any snippet or command — so it is mostly rather than fully executable.

4 / 5

Workflow Clarity

The Phase 0→5 sequence is explicit with real validation checkpoints at each stage: privacy masking before analysis, non-comparability marking, pre-registered A/B analysis decisions, stop/rollback rules on every budget scenario, changes gated as 'proposals unless separately authorized', and monitor→re-evaluate feedback loops plus checklists in the action plan — matching the anchor for explicit validation, feedback loops, and checklists.

5 / 5

Progressive Disclosure

No bundle files exist; everything is inline in a single ~370-line file. Sections are well organized, but the Phase 5 output template and per-platform format tables are natural candidates for separate reference files that are not split out, fitting 'content that should be separate is inline'. It is not a 2 because structure and headers are clear and nothing is buried.

3 / 5

Total

15

/

20

Passed

Description

58%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 states concrete, well-hedged capabilities in third person with an appropriately scoped anti-overclaim ('without overstating causality'), but it omits any 'Use when...' trigger guidance and never uses the words users naturally say ('ads', 'Google Ads', 'Meta Ads', 'ROAS', 'CPA'). Adding an explicit trigger clause naming the platforms and metrics would lift both completeness and trigger-term quality.

Suggestions

Add a 'Use when...' clause with concrete triggers, e.g. 'Use when the user asks about ad campaign performance, budget allocation, or where to cut ad spend across Google, Meta, or LinkedIn.'

Include the natural user vocabulary the body already covers: 'ads', 'Google Ads', 'Meta Ads', 'ad spend', 'ROAS', 'CPA' — currently none of these terms appear in the description.

Briefly enumerate the skill's main outputs (performance diagnostics, funnel analysis, budget reallocation, A/B test evaluation) to close the gap between the generic 'analyze' verb and the body's actual scope.

DimensionReasoningScore

Specificity

Names several concrete third-person actions — 'Analyze cross-channel campaign data', 'quantify uncertainty', 'propose evidence-labeled budget tests' — but the analysis actions stay generic relative to the body's actual coverage (diagnostics, funnel analysis, reallocation, reporting), so it falls between anchors 4 and 5 rather than achieving comprehensive coverage.

4 / 5

Completeness

The 'what' is clear and concrete, but there is no 'Use when...' clause or equivalent explicit trigger guidance anywhere in the description, which caps completeness at 3 per the judging guidelines. It is not a 2 because the 'what' is explicit rather than vague.

3 / 5

Trigger Term Quality

'cross-channel campaign data' and 'budget tests' are relevant keywords, but the natural phrases users actually say — 'Google Ads', 'Meta Ads', 'ad spend', 'ROAS', 'CPA', and even the words 'ads'/'advertising' — are absent, matching the anchor for relevant keywords with missing common variations.

3 / 5

Distinctiveness Conflict Risk

'Cross-channel campaign data' and 'evidence-labeled budget tests' define a fairly narrow ad-marketing niche with minor overlap risk against closely related marketing-analytics skills. It is not a 5 because without trigger phrases or channel names it could still fire for generic data-analysis or non-advertising campaign requests.

4 / 5

Total

14

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

sickn33/agentic-awesome-skills

Path

plugins/agentic-awesome-skills-claude/skills/ad-campaign-analyzer/SKILL.md

Reviewed

Table of Contents

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