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webshop-query-interpreter

Interprets a user's shopping query to extract key product requirements such as item type, attributes, and constraints. Use when a new shopping instruction is received and you need to parse natural language into structured criteria (product category, desired features, price limits) before performing a search. The output is a clear set of search parameters for use in subsequent product lookup steps.

69

Quality

84%

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SKILL.md
Quality
Evals
Security

Quality

Content

85%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 concise, highly actionable skill with a clear three-step workflow and concrete output templates plus worked examples — the core instruction quality is high. The notable defect is progressive disclosure: two reference files ship in the bundle but are completely unreferenced from SKILL.md, so the parser never sees the linguistic patterns and edge cases they contain.

Suggestions

Add a short '## Reference' section linking references/query_patterns.md (e.g., 'For constraint phrasings, currency formats, and ambiguous queries, see [query_patterns.md](references/query_patterns.md)') so the bundle's pattern catalog is discoverable.

Fold the key edge cases (multiple products, negation, price ranges) into the Parse step or point to the reference for them, since the current examples only cover straightforward queries.

Consider linking references/execution_example.md as the end-to-end worked example and dropping one of the two inline examples to trim the mild redundancy.

DimensionReasoningScore

Conciseness

The body is lean — a short Trigger section, a three-step process with a compact output template, and two worked examples — and assumes Claude's competence without explaining parsing concepts. It is not a 5 because the 'Thought:' walk-throughs in both examples re-explain the extraction the Core Process steps and template already specify, and the second example only marginally adds over the first (quantity handling).

4 / 5

Actionability

The guidance is fully concrete and copy-paste ready for an instruction-only skill: a fill-in output template ('Product Type: <primary item> / Attributes: ... / Constraints: ... / Search Query: ...'), two complete worked examples with final structured outputs, and a specific handoff naming downstream skills ('webshop-search-executor' or 'webshop-product-search'). The examples cover the common cases (attribute-heavy query and quantity-plus-attribute query), matching the anchor-5 standard.

5 / 5

Workflow Clarity

The three-step sequence (Parse the Instruction → Structure the Output → Hand Off) is clearly ordered with each step's inputs, mechanics, and output format specified; the simple-skill exception applies since this is a single non-destructive parsing task with an unambiguous action. It is not a 4 because no validation checkpoints are needed for a non-destructive, non-batch parse-and-format operation, and the per-field extraction checklist inside step 1 acts as an implicit completeness check.

5 / 5

Progressive Disclosure

The body itself is well organized into short sections, but the bundle's reference files (references/query_patterns.md, which catalogs constraint phrasings, currency formats, and edge cases, and references/execution_example.md) are never mentioned or linked anywhere in SKILL.md — they are orphaned from navigation entirely. This lands at anchor 3 ('references present but not clearly signaled'): structure exists, but provided reference material that would materially aid parsing is invisible to a reader of the skill, which is worse signaling than the clearly-linked anchor 4 while the body remains too well organized for anchor 2.

3 / 5

Total

17

/

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 explicitly covers what the skill does and when to use it, with mostly natural trigger terms and a distinct parsing niche. Its weaknesses are modest: some redundancy in the final sentence and missing common shopping phrasings like 'buy', 'purchase', or 'under $X' that users actually say.

Suggestions

Add one or two natural user phrasings to the trigger clause (e.g., 'Use when the user says they want to buy, find, or look for a product...') to strengthen trigger_term_quality.

Trim the final sentence ('The output is a clear set of search parameters for use in subsequent product lookup steps') or merge it into the first sentence to remove restatement and tighten specificity.

DimensionReasoningScore

Specificity

The description lists several concrete actions in third person — 'Interprets a user's shopping query to extract key product requirements such as item type, attributes, and constraints' and 'parse natural language into structured criteria (product category, desired features, price limits)' — covering the full input-to-output pipeline. It stops short of a 5 because the closing sentence ('The output is a clear set of search parameters...') restates the previous action rather than adding new capability, which is minor padding rather than comprehensive coverage.

4 / 5

Completeness

Both questions are answered explicitly: the 'what' is 'extract key product requirements such as item type, attributes, and constraints', and the 'when' is a concrete 'Use when a new shopping instruction is received and you need to parse natural language into structured criteria ... before performing a search'. The when-clause names the triggering situation, the precondition, and the position in the workflow, matching the anchor-5 example's structure.

5 / 5

Trigger Term Quality

Good natural keyword coverage: 'shopping query', 'shopping instruction', 'product requirements', 'price limits', 'search parameters' are phrases a user or orchestrator would plausibly say. It is not a 5 because common shopping-trigger variations users actually say — 'buy', 'purchase', 'find me', 'I need/want', 'under $X' — are absent, though it clearly exceeds the sparse keyword sets at anchor 3.

4 / 5

Distinctiveness Conflict Risk

The parsing/interpretation niche ('interprets a user's shopping query ... before performing a search') is clearly distinct from generic skills, but 'before performing a search' and 'product lookup steps' create minor overlap risk with closely related search-execution skills in the same webshop workflow. It is not a 5 because a user message about searching for products could plausibly match both this and a search-executor skill.

4 / 5

Total

17

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
zjunlp/SkillNet
Reviewed

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