sn-image-base

Base-layer skill for the SenseNova-Skills project, providing low-level APIs for image generation, recognition (VLM), and text optimization (LLM). This skill does not preprocess inputs; it only calls backend services and returns results. This skill is not user-facing and is intended for upper-layer skills only.

Quality

61%

Does it follow best practices?

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Securityby

High

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tessl review fix ./skills/sn-image-base/SKILL.md

Quality

Content

72%

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

A well-structured, highly actionable reference with a clean one-level reference split; its main weakness is repetition of the env-var/default tables and the absence of explicit validation or error-recovery checkpoints.

Dimension	Reasoning	Score
Conciseness	The body is dense and avoids explaining concepts Claude already knows, but the env-var fallback chain for api-key/base-url/model/type is repeated across the Tools List tables, the Default Parameter Behavior section, and the Agent Configuration section, so it could be tightened.	2 / 3
Actionability	Provides fully executable, copy-paste-ready commands ("pip install -r requirements.txt", "python scripts/sn_agent_runner.py sn-image-generate --prompt \"...\"") with concrete flags and parameter tables giving types, defaults, and env vars.	3 / 3
Workflow Clarity	The install → invoke → parse-output sequence is clear, but there are no explicit validation checkpoints or recovery guidance beyond showing the failure JSON format, so checkpoints remain implicit.	2 / 3
Progressive Disclosure	The body is an organized overview that points to a real one-level-deep reference ("See `references/api_spec.md` for details", verified to exist) and to the runner script, keeping detailed API spec off the main page.	3 / 3
	Total	10 / 12 Passed

Description

50%

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 clearly identifies the skill's role and capabilities but lacks an explicit "Use when..." trigger clause and relies on jargon-heavy terms, leaving every dimension at the mid-level anchor.

Suggestions

Add an explicit trigger clause, e.g. "Use when an upper-layer SenseNova-Skills skill needs low-level image generation, image recognition, or text optimization."

Replace jargon-only terms with natural variations users would say (e.g. add "image generation, image recognition/description, text rewriting" alongside VLM/LLM).

State the distinct trigger condition more sharply so it cannot be confused with higher-tier user-facing image skills.

Dimension	Reasoning	Score
Specificity	Names the domain and three concrete capabilities ("image generation, recognition (VLM), and text optimization (LLM)"), but the actual actions are framed generically as "providing low-level APIs" and "calls backend services and returns results" rather than as concrete verbs, so it stops short of a comprehensive action list.	2 / 3
Completeness	It clearly states what the skill does, but the "when" is only implied via "intended for upper-layer skills only" with no "Use when..." clause, which per the rubric caps completeness at 2.	2 / 3
Trigger Term Quality	Contains one natural term ("image generation") but pairs it with jargon ("recognition (VLM)", "text optimization (LLM)") and omits common variations, so keyword coverage is partial rather than complete.	2 / 3
Distinctiveness Conflict Risk	Scoping to the SenseNova-Skills base layer ("tier 0", "not user-facing") gives it a niche, but the broad image/VLM/LLM capability set and absence of distinct trigger phrasing leave real overlap risk with sibling skills.	2 / 3
	Total	8 / 12 Passed

Validation

81%

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 — 13 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
metadata_field	'metadata' should map string keys to string values	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Repository: OpenSenseNova/SenseNova-Skills
Path: skills/sn-image-base/SKILL.md
Commit: 179fea1

Reviewed: 2 days ago

Table of Contents

Discovery Implementation Validation

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