pdf-text-extraction-fallback-85d5ca

Fallback workflow for extracting text from PDFs when read_file returns binary data

Quality

65%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./benchmarks/gdpval/skills/pdf-text-extraction-fallback-85d5ca/SKILL.md

Quality

Content

62%

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

The body gives a clear, validated multi-step fallback workflow with concrete tools and error recovery, but loses points to a redundant full code example and pseudocode orchestration that could be tightened or made executable.

Suggestions

Remove the standalone 'Code Example' section or trim it to avoid duplicating the step-by-step flow and reduce token cost.

Make the orchestration example genuinely executable (e.g., real subprocess calls to pdftotext) rather than treating read_file/shell_agent as Python functions.

Drop filler sentences like 'This workflow provides a reliable fallback using command-line PDF tools' since the steps already convey this.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with concrete tool names, but the full 'Code Example' section restates the step-by-step flow and the Tips repeat earlier points, so it could be tightened; minor filler like 'This workflow provides a reliable fallback...' adds little.	2 / 3
Actionability	Provides specific shell_agent task strings, a real executable validation function, and named tools, but the central orchestration example treats tools as Python functions with result.stdout, which is pseudocode rather than copy-paste-ready executable code.	2 / 3
Workflow Clarity	Steps 1-5 are clearly sequenced with an explicit validation checkpoint (Step 3) and a feedback loop for error recovery (Step 4: try alternative tool, try OCR, report error).	3 / 3
Progressive Disclosure	No bundle files exist and the skill is a single ~135-line file with clean sections, but it is somewhat monolithic with the redundant full code example inline rather than split out or trimmed.	2 / 3
	Total	9 / 12 Passed

Description

67%

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 is concise and answers both what and when with an explicit (if technical) trigger, but its trigger terms are narrow and it risks overlapping with general PDF extraction skills.

Suggestions

Add user-facing trigger phrasing (e.g., 'Use when the user needs text from a PDF and read_file returns binary or garbled data') to broaden natural keyword coverage.

List the concrete actions or fallback tools (e.g., pdftotext, pdfplumber, OCR) to raise specificity and distinguish it from a general PDF skill.

Include common variations like 'PDF files', '.pdf', and 'document extraction' to improve trigger term quality.

Dimension	Reasoning	Score
Specificity	Names the domain and one concrete action ('extracting text from PDFs') plus a fallback condition, but lists a single action rather than multiple specific concrete actions, so it is not comprehensive.	2 / 3
Completeness	Explicitly states what it does ('Fallback workflow for extracting text from PDFs') and when to use it ('when read_file returns binary data'), so both what and when are answered with an explicit trigger.	3 / 3
Trigger Term Quality	Includes a natural phrase ('extracting text from PDFs', 'PDFs') but the trigger leans on a tool name ('read_file returns binary data') and misses common variations like 'PDF files', 'document extraction', or '.pdf'.	2 / 3
Distinctiveness Conflict Risk	The fallback framing is a clear niche, but 'extracting text from PDFs' is a broad domain that could overlap with a general PDF-text-extraction skill.	2 / 3
	Total	9 / 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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: HKUDS/OpenSpace
Path: benchmarks/gdpval/skills/pdf-text-extraction-fallback-85d5ca/SKILL.md
Commit: c5a9c4b

Reviewed: 2 days ago

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