ocr
Extract text from images using Tesseract OCR
61
52%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./examples/skill/skills/ocr/SKILL.mdQuality
Discovery
40%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 identifies a clear niche (Tesseract OCR on images) which makes it distinctive, but it is too terse. It lacks a 'Use when...' clause, lists only one action, and misses common user-facing trigger terms like 'scan', 'image to text', or file extensions.
Suggestions
Add a 'Use when...' clause with explicit triggers, e.g., 'Use when the user asks to read text from an image, scan a document image, or convert image to text.'
Include natural trigger term variations such as 'scan', 'image to text', 'read text from picture', '.png', '.jpg', '.tiff', 'optical character recognition'.
List additional concrete capabilities beyond 'extract text', such as 'supports multiple languages, handles scanned documents, processes batch images'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (images, OCR) and one action (extract text), but only describes a single capability rather than listing multiple concrete actions like supported formats, batch processing, or language options. | 2 / 3 |
Completeness | Describes what the skill does but completely lacks a 'Use when...' clause or any explicit trigger guidance, which per the rubric caps completeness at 2, and since the 'what' is also minimal, a score of 1 is appropriate. | 1 / 3 |
Trigger Term Quality | Includes relevant keywords like 'images', 'Tesseract', and 'OCR' that users might say, but misses common variations like 'scan', 'read text from image', 'image to text', '.png', '.jpg', or 'optical character recognition'. | 2 / 3 |
Distinctiveness Conflict Risk | The mention of 'Tesseract OCR' and 'images' creates a clear, distinct niche that is unlikely to conflict with other skills; the technology and task are very specific. | 3 / 3 |
Total | 8 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides clear, actionable CLI commands for OCR text extraction with good coverage of options and languages. Its main weaknesses are token inefficiency from including information Claude already knows (installation steps, language codes, dependency lists) and lack of validation/error-handling guidance for when OCR produces poor results or dependencies are missing.
Suggestions
Remove the Dependencies, Installation, and Supported Image Formats sections — Claude already knows how to install packages and which formats are common image types.
Trim the language table to just 2-3 examples inline, or remove it entirely since language codes are well-known.
Add brief error handling guidance: what to do if OCR output is poor (try --preprocess, check image quality) or if Tesseract is not found.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content includes some unnecessary sections like the language table, supported image formats list, and dependencies/installation instructions that Claude already knows or can infer. The capabilities bullet list is also somewhat redundant given the usage examples. However, it's not egregiously verbose. | 2 / 3 |
Actionability | The skill provides fully concrete, copy-paste ready bash commands with clear parameter explanations. Every usage pattern is demonstrated with specific executable examples covering basic usage, language options, preprocessing, and URL-based OCR. | 3 / 3 |
Workflow Clarity | This is essentially a single-command tool, so complex workflows aren't strictly needed. However, there's no validation or error handling guidance — what happens if Tesseract isn't installed, if the image is unreadable, or if OCR produces poor results? For a tool that can produce unreliable output, some guidance on verifying results or handling failures would be valuable. | 2 / 3 |
Progressive Disclosure | The content is reasonably structured with clear sections, but the language table, dependencies, and installation instructions bloat the main file. These could be referenced externally or omitted entirely since Claude can look them up. The content is all inline with no references to supplementary files. | 2 / 3 |
Total | 9 / 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.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- trpc-group/trpc-agent-go
- Commit
fcc550d
- Reviewed
Table of Contents
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