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gift-evaluator

The PRIMARY tool for Spring Festival gift analysis and social interaction generation. Use this skill when users upload photos of gifts (alcohol, tea, supplements, etc.) to inquire about their value, authenticity, or how to respond socially. Integrates visual perception, market valuation, and HTML card generation.

59

Quality

67%

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/gift-evaluator/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

35%

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

The skill provides a creative and well-structured framework for gift appraisal with a clear four-phase workflow and a concrete HTML generation command. However, it suffers from significant verbosity with metaphorical framing that wastes tokens, vague tool references in early phases, and missing validation/error-handling steps. The content would benefit from trimming conceptual explanations and adding specific tool names and verification checkpoints.

Suggestions

Remove verbose metaphorical framing ('The Eye', 'The Brain', 'The Mouth') and the introductory paragraph explaining what the skill does—start directly with actionable instructions.

Specify exact tool names and commands for the perception and search phases instead of vague references like 'Call the vision tool' and 'Use search tools'.

Add validation checkpoints: verify vision extraction produced usable keywords before searching, verify search returned pricing data before structuring content, and verify HTML file was generated successfully before presenting the path.

Include the html_tools.py script in the bundle or reference its location explicitly, and add a brief note on expected output/error handling for the generate_gift_card command.

DimensionReasoningScore

Conciseness

The skill is verbose with unnecessary conceptual framing ('The Eye', 'The Brain', 'The Mouth'), explains things Claude already knows (what VLM skills are, how to read raw strings), and includes padding like 'This skill transforms the assistant into...' and 'It bridges the gap between raw visual data and complex social context.' Much of the introductory and phase-description text could be eliminated.

1 / 3

Actionability

The HTML generation command is concrete and copy-paste ready with clear parameter structure, and the JSON formats are specified. However, the perception and search phases are vague ('Call the vision tool', 'Use search tools'), lacking specific tool names or executable commands. The search command format is incomplete pseudo-syntax.

2 / 3

Workflow Clarity

The four phases are clearly sequenced and logically ordered. However, there are no validation checkpoints—no step to verify the HTML was generated correctly, no error handling if search returns no results, no feedback loop if the vision tool fails to extract brand names. For a multi-step workflow involving file generation, this is a significant gap.

2 / 3

Progressive Disclosure

The content is structured with clear sections and phases, which is good. However, it's a monolithic document with no references to external files despite referencing html_tools.py (no bundle files provided). The inline JSON format specifications and detailed HTML command could potentially be split out, and the lack of any supporting documentation makes this a single wall of instructions.

2 / 3

Total

7

/

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.

This is a strong description that clearly defines a specific niche (Spring Festival gift analysis), lists concrete actions and capabilities, includes natural trigger terms, and explicitly states when to use the skill. The description is concise yet comprehensive, covering the what, when, and how effectively. Minor note: 'The PRIMARY tool' is slightly assertive phrasing but doesn't detract significantly from clarity.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: gift analysis, social interaction generation, visual perception, market valuation, HTML card generation. Also provides concrete examples of gift types (alcohol, tea, supplements).

3 / 3

Completeness

Clearly answers both what ('gift analysis and social interaction generation', 'visual perception, market valuation, and HTML card generation') and when ('when users upload photos of gifts to inquire about their value, authenticity, or how to respond socially').

3 / 3

Trigger Term Quality

Includes natural keywords users would say: 'photos of gifts', 'alcohol, tea, supplements', 'value', 'authenticity', 'respond socially', 'Spring Festival'. These are terms a user would naturally use when uploading gift photos for analysis.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive niche combining Spring Festival context, gift photo analysis, valuation, and social response generation. Very unlikely to conflict with other skills due to its specific cultural and functional scope.

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
jjyaoao/HelloAgents
Reviewed

Table of Contents

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