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online-shopping

Research any online purchase with DeepAPI — fair-price checks, best deals, where to buy, shop trust. Load whenever the user is shopping or buying anything online: mentions buying a product, comparing prices, "is this a good price", "where can I get X", or attaches a product photo or listing screenshot. Research only — never places orders.

75

Quality

92%

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SKILL.md
Quality
Evals
Security

Quality

Content

85%

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

The body is highly actionable with concrete curl examples, an endpoint cost table, and a copy-paste answer template, plus a clear validated workflow. Its only weakness is mild verbosity from repeated emphasis lines and an off-task model recommendation.

Suggestions

Remove the "Fable 5 model" recommendation line — it is not actionable guidance for executing the skill and adds tokens that do not earn their place.

Consolidate the repeated emphasis on conciseness/format into a single hard-rule statement; "Non-negotiable...", "The format below is a hard rule, not a preference", and the closing "Success looks like this" all restate the same contract.

Tighten the price-tier section by merging the tier definitions into the existing bullet list rather than restating the "cheap item researched for minutes is this skill failing" framing twice.

DimensionReasoningScore

Conciseness

Mostly efficient with no concept-explaining padding, but it could be tightened: the "Fable 5 model" recommendation adds little actionable value, and repeated emphasis lines ("Non-negotiable", "The format below is a hard rule, not a preference", "Success looks like this...") restate the same constraint multiple times.

2 / 3

Actionability

Fully concrete and copy-paste ready: a complete curl example with auth headers and Idempotency-Key, an endpoint table with maxCostUsd budgets, and an exact markdown answer template to follow.

3 / 3

Workflow Clarity

Clear sequence — setup, mandatory first-impressions opener, price-tiered research depth, then a fixed answer format with an explicit validation gate ("check every response against it before sending").

3 / 3

Progressive Disclosure

A single ~90-line file with well-organized sections and no external references; per the simple-skills scoring note this is appropriately structured without needing separate files.

3 / 3

Total

11

/

12

Passed

Description

100%

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 specific, trigger-rich, and complete, clearly answering both what the skill does and when to load it with natural phrasing. It is concise without padding and well-scoped against conflicting skills.

DimensionReasoningScore

Specificity

Names multiple concrete actions — "fair-price checks, best deals, where to buy, shop trust" — matching the anchor for listing several specific concrete actions.

3 / 3

Completeness

Explicitly answers what (research any online purchase: fair price, where to buy, shop trust) and when ("Load whenever the user is shopping or buying anything online..."), with an explicit Use-when clause.

3 / 3

Trigger Term Quality

Excellent natural trigger coverage: "buying a product, comparing prices, 'is this a good price', 'where can I get X', or attaches a product photo or listing screenshot" — phrases users would actually say.

3 / 3

Distinctiveness Conflict Risk

A clear niche (online shopping research via DeepAPI) with distinct triggers and a boundary clause ("Research only — never places orders") that reduces conflict with order-placement skills.

3 / 3

Total

12

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
mishatojk/davidskills
Reviewed

Table of Contents

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