ParseJet - Universal File & URL Parser
Server Quality Checklist
Latest release: v0.1.1
- Disambiguation4/5
Tools mostly distinct: parse_file handles local files, parse_url handles any URL, get_youtube_transcript is specialized for YouTube transcripts. There is slight overlap between get_youtube_transcript and parse_url for YouTube videos, but descriptions clarify different intents.
Naming Consistency4/5Two tools follow a parse_* pattern, while get_youtube_transcript breaks consistency with a get_ prefix. This is a minor deviation but still understandable.
Tool Count3/53 tools for a 'Universal File & URL Parser' feels slightly thin but not unreasonable. The scope is covered by the two parse tools, with the transcript tool as an additional feature.
Completeness4/5Core functionality (parsing local files and URLs) is covered. Missing explicit tools for structured data parsing (e.g., JSON, XML) but the parse_file and parse_url tools claim broad support. Minor gaps but adequate for common tasks.
Average 3.2/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions the external dependency (ParseJet) but fails to disclose critical behaviors such as file size limits, supported formats beyond examples, error handling, or whether it modifies the file. This is insufficient for safe agent use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no fluff. However, it could be marginally improved by front-loading the action and separating the method detail for quicker comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of file parsing and the absence of an output schema, the description should specify the return value (e.g., extracted text). It only says 'extracting its content' but lacks details on format, size, or potential failures. The description feels incomplete for an agent to fully understand the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds 'local file' context but does not elaborate on the parameters beyond what the schema already provides, such as constraints or usage tips.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Parse' and the resource 'local file', listing supported types (PDF, DOCX, image, etc.) and the method (uploading to ParseJet). It effectively distinguishes from sibling tools that handle URLs or transcripts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like parse_url or get_youtube_transcript. It does not mention any prerequisites, limitations, or contexts where the tool is inappropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits, but it only states 'Get the transcript' without mentioning side effects, error cases (e.g., missing transcript), or limitations (e.g., rate limits, language availability).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded and contains no extraneous information, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description should provide more context about return values, error handling, or output format (e.g., segments with text and timestamps). The current one-liner is insufficient for a tool with two parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents parameters. The description adds minimal value by confirming 'language' is optional, but does not provide further semantic enrichment beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get'), the resource ('transcript of a YouTube video'), and the optional language parameter, effectively distinguishing it from sibling tools like 'parse_file' and 'parse_url'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any prerequisites (e.g., video must have captions, no authentication requirements). The description lacks contextual usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description alone must disclose behavioral traits. It states that content is extracted as text or markdown, but it does not mention limitations (e.g., size limits, authentication needs, rate limits, or handling of dynamic content). This lack of detail leaves the agent uncertain about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the purpose. Every word adds value—'Parse any URL', examples, and output format. No unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and no output schema, the description is adequate but lacks details on error handling, content limitations, or behavior with different URL types. An AI agent might need more context (e.g., this may not handle login-required content). Sufficient for basic use, but gaps exist.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with descriptions: url (string, uri) and output_format (enum, default). The description adds no new information beyond what the schema provides. It mentions 'text or markdown' which is already in the enum. Baseline 3 applies due to high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: parsing any URL (web pages, YouTube, PDFs) and extracting content as text or markdown. The verb 'Parse' and resource 'URL content' are specific, and the list of examples distinguishes it from sibling tools like get_youtube_transcript and parse_file.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description suggests a broad use case but provides no explicit guidance on when to use this tool versus its siblings (get_youtube_transcript, parse_file). For instance, it mentions YouTube and PDFs, but those have specialized tools. No 'when not to use' or alternative recommendations are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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