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bid-optimization

Recommends bid adjustments based on performance data. Use for CPC optimization, budget allocation, ROAS improvement, day-parting, device modifiers, and audience bid strategies.

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./skills/bid-optimization/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

56%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 skill body is well-structured with a clear sequenced workflow and concrete thresholds, but it is undermined by referencing scripts and template files that are absent from the bundle, a promotional footer that wastes tokens, and duplicated safety-bounds content. These issues make the otherwise actionable guidance non-executable as shipped.

Suggestions

Ship the referenced files (scripts/analyze-bids.py, scripts/generate-script.py, and the three templates/*.js files) in the bundle, or inline the essential logic so the commands are actually executable.

Remove the promotional 'About this skill' footer and the UTM-tagged marketing links from SKILL.md; they consume tokens without helping skill execution.

Consolidate the bid modifier bounds into the single 'Bid Modifier Bounds' section instead of restating the -90% to +300% range under Device Modifiers.

Add an error-recovery step after 'Preview before running' describing what to check and how to fix issues before scheduling the script.

DimensionReasoningScore

Conciseness

Strategy and bounds sections are appropriately terse, but the ~10-line promotional footer ("Want this skill (and 40+ more) running on autopilot... Try Synter" with UTM-tagged links) is pure padding, and bid modifier bounds are stated twice ("-90% to +300%" appears in both Device Modifiers and Bid Modifier Bounds sections) — unnecessary content beyond the 'minor instances' of the 4 anchor.

3 / 5

Actionability

Commands are concrete and flag-specific ("python scripts/analyze-bids.py --input campaign_data.csv --output recommendations.json") with explicit thresholds ("CPA > target × 1.3", "95%"), but the two referenced scripts and all three templates are absent from the bundle, so the workflow's core commands cannot actually execute — a missing-key-details gap that the 'minor gaps' of 4 does not cover.

3 / 5

Workflow Clarity

The four-step workflow (Analyze → Review → Generate → Deploy) is clearly sequenced with concrete commands and checkpoints ("Preview before running", manual approval guardrails), but there is no error-recovery feedback loop (e.g., what to do if the preview or recommendations look wrong), keeping it below the explicit-validation 5 anchor.

4 / 5

Progressive Disclosure

The body is well-organized into clear sections, but every external reference — "scripts/analyze-bids.py", "scripts/generate-script.py", and the three files in "templates/" — points to files that do not exist in the bundle, leaving navigation to dead ends; structure is present but the missing referenced files prevent a higher score.

3 / 5

Total

13

/

20

Passed

Description

83%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 clearly states what the skill does and when to use it, with domain-native trigger terms. Its main weaknesses are the missing platform qualifier (Google Ads) and absent common synonyms like PPC or paid search, which slightly limit both specificity and trigger coverage.

DimensionReasoningScore

Specificity

Lists several specific capabilities ("CPC optimization, budget allocation, ROAS improvement, day-parting, device modifiers, and audience bid strategies") alongside the core action "Recommends bid adjustments based on performance data", but never names the platform (Google Ads), leaving minor gaps in coverage that keep it below the comprehensive 5 anchor.

4 / 5

Completeness

Explicitly answers both questions: "Recommends bid adjustments based on performance data" (what) and "Use for CPC optimization, budget allocation, ROAS improvement, day-parting..." (when) with concrete trigger phrases, matching the 5 anchor; not 4 because the when-clause is already explicit and specific, not merely present.

5 / 5

Trigger Term Quality

"CPC optimization", "ROAS improvement", "day-parting", and "device modifiers" are natural terms practitioners would actually say, but common synonyms like "Google Ads", "PPC", or "paid search" are missing, matching the 'good keyword coverage; a few natural terms missing' anchor rather than comprehensive coverage.

4 / 5

Distinctiveness Conflict Risk

Niche bidding vocabulary ("day-parting", "ROAS", "device modifiers") establishes a clear trigger territory with minimal conflict risk, but the generic "budget allocation" could overlap with general marketing-budget skills, fitting 'mostly distinct; minor overlap risk' rather than the minimal-risk 5 anchor.

4 / 5

Total

17

/

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

referenced_paths_exist

Referenced path issues: 4 missing

Warning

Total

15

/

16

Passed

Repository

Synter-Media-AI/free-skills

Path

skills/bid-optimization/SKILL.md

Reviewed

Table of Contents

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