shogun-screenshot
スクリーンショットの取得・加工を行う。ローカルスクショから最新画像を取得、 PlaywrightでWebページをキャプチャ、画像のトリミング・リサイズ、機微情報を黒塗りマスキング。 記事執筆、レポート作成、UI確認、画像加工時に起動。 「スクショ」「スクリーンショット」「画面キャプチャ」「最新のスクショ」「画像加工」「トリミング」「マスク」「写メ」「写メ撮った」「スクショ撮った」で起動。 Do NOT use for: 画像生成（shogun-imagegenを使え）。
89
88%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
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 an excellent skill description that covers all key dimensions thoroughly. It lists specific concrete capabilities, provides extensive natural-language trigger terms (including colloquial Japanese variations), clearly delineates both 'what' and 'when', and explicitly distinguishes itself from a related skill (image generation). The use of third person voice and concise structure makes it highly effective for skill selection.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: retrieving latest screenshots from local storage, capturing web pages with Playwright, trimming/resizing images, and masking sensitive information with black overlay. | 3 / 3 |
Completeness | Clearly answers both 'what' (screenshot capture, web page capture via Playwright, trimming/resizing, masking) and 'when' (記事執筆、レポート作成、UI確認、画像加工時 plus explicit trigger terms). Also includes a 'Do NOT use for' clause to prevent misuse, which adds clarity. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms in Japanese including colloquial variations: 「スクショ」「スクリーンショット」「画面キャプチャ」「最新のスクショ」「画像加工」「トリミング」「マスク」「写メ」「写メ撮った」「スクショ撮った」. These are terms users would naturally say. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche (screenshot capture and image processing), explicit trigger terms, and an explicit exclusion clause directing image generation to a different skill (shogun-imagegen), minimizing conflict risk. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, actionable skill with well-structured multi-mode workflows and concrete executable commands. Its main weakness is some unnecessary content (North Star philosophy, When to Use triggers) that consumes tokens without adding operational value. The masking workflow with preview validation is particularly well-designed.
Suggestions
Remove the 'North Star' and 'When to Use' sections — these are meta-information that belongs in frontmatter or description, not in the operational skill body.
Consider splitting detailed mode instructions into separate referenced files (e.g., modes/masking.md) to keep the main SKILL.md as a concise overview with navigation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The 'North Star' section and 'When to Use' section add little actionable value and could be removed. The 'Configuration' section is useful but the overall content has some padding (e.g., explaining when to use the skill, which is already covered in frontmatter). However, it's not egregiously verbose. | 2 / 3 |
Actionability | Each mode provides concrete, executable commands with specific script paths, CLI arguments, and options. The masking mode is particularly well-documented with single/multiple region examples and a preview workflow. Code is copy-paste ready. | 3 / 3 |
Workflow Clarity | Mode 4 (masking) has an explicit validation workflow: preview with red outlines → confirm coordinates → execute actual masking. Mode 1 has clear fallback logic with ordered path exploration. Multi-step processes are clearly sequenced with numbered steps. | 3 / 3 |
Progressive Disclosure | The content is reasonably structured with clear section headers and mode separation, but everything is inline in a single file. References to helper scripts (capture_local.sh, trim_image.py, mask_sensitive.py) exist but no bundle files are provided to verify them. The config reference is good but the file is somewhat long for a single SKILL.md. | 2 / 3 |
Total | 10 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Repository
- yohey-w/multi-agent-shogun
- Commit
4ee1377
- Reviewed
Table of Contents
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