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.

Quality

63%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/gift-evaluator/SKILL.md

Quality

Discovery

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 distinctly enough to avoid conflicts with other skills.

Dimension	Reasoning	Score
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

Implementation

27%

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

The skill has a clear four-phase workflow structure and provides some concrete guidance (price thresholds, JSON formats, CLI command), but suffers from significant verbosity with unnecessary metaphors and abstract framing. The lack of validation steps in a multi-step generation pipeline and the absence of bundle files supporting the referenced html_tools.py weaken its reliability. Tool references in the perception and search phases are too vague to be directly actionable.

Suggestions

Remove the introductory paragraph and metaphorical labels ('The Eye', 'The Brain', 'The Mouth'); start directly with the workflow steps to improve conciseness.

Specify exact tool names and executable commands for the vision analysis and search phases instead of vague references like 'Call the vision tool'.

Add validation checkpoints: verify JSON is well-formed before passing to html_tools.py, and check that the output HTML file was created successfully with error recovery steps.

Include html_tools.py as a bundle file or provide its interface documentation so the CLI command can be verified, and consider splitting JSON schema details into a reference file.

Dimension	Reasoning	Score
Conciseness	The opening paragraph explains what the skill does in abstract terms ('bridges the gap between raw visual data and complex social context') which is unnecessary preamble. The 'Agent Thinking Strategy' section uses metaphors like '(The Eye)', '(The Brain)', '(The Mouth)' that add no value. Multiple sections restate purposes redundantly, and concepts like 'High EQ' and 'Market-Savvy mindset' are vague filler.	1 / 3
Actionability	The skill provides a concrete CLI command for html_tools.py with specific parameters, JSON format examples, and price classification thresholds, which is useful. However, the vision and search phases are vague ('Call the vision tool', 'Use search tools') without specifying exact tool names or executable commands. The search command format is incomplete and not copy-paste ready.	2 / 3
Workflow Clarity	The four phases are clearly sequenced (Perception → Valuation → Structuring → Creation), which provides good structure. However, there are no validation checkpoints—no step to verify the search results are accurate, no validation that the JSON is well-formed before passing to the HTML generator, and no error recovery if html_tools.py fails. For a multi-step pipeline involving file generation, this is a significant gap.	2 / 3
Progressive Disclosure	All content is in a single monolithic file with no references to external documentation. The skill references 'html_tools.py' but no bundle files are provided, meaning there's no way to verify the tool exists or its interface. The JSON schema details and HTML generation specifics could be split into reference files, but instead everything is inline with no navigation structure.	1 / 3
	Total	6 / 12 Passed

Validation

100%

Warnings & errors only

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

Validation — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: jjyaoao/HelloAgents
Commit: 52b2597

Reviewed: 14 days ago

Table of Contents

Discovery Implementation Validation

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