open_graph_checker
Analyze and validate Open Graph meta tags on any webpage to ensure proper social media sharing and preview display.
Instructions
Open Graph Checker
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Example value: facebook.com |
Analyze and validate Open Graph meta tags on any webpage to ensure proper social media sharing and preview display.
Open Graph Checker
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Example value: facebook.com |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Open Graph Checker' implies a read-only analysis tool, but it doesn't specify whether it performs HTTP requests, requires authentication, has rate limits, returns structured data, or handles errors. For a tool with no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise with just three words, this is under-specification rather than effective brevity. The description is too terse to be helpful—it doesn't front-load key information or use its limited space to clarify the tool's function. Every word should earn its place, but here the words don't provide meaningful context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's likely complexity (analyzing Open Graph Protocol tags), no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how it behaves, or its use cases. For a tool that presumably makes network requests and returns structured data about meta tags, this description leaves critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with the 'url' parameter clearly documented. The description adds no additional parameter semantics beyond what the schema provides. With high schema coverage, the baseline score is 3, as the description doesn't need to compensate but also adds no value regarding parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Open Graph Checker' is a tautology that restates the tool name without specifying what it actually does. It doesn't mention what 'Open Graph' refers to (likely Open Graph Protocol meta tags for social media sharing) or what 'checking' entails (validation, extraction, analysis). Compared to sibling tools like 'meta_tags_analyzer' or 'serp_api', it fails to distinguish its specific purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does 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. It doesn't mention context (e.g., for social media optimization, SEO analysis), prerequisites, or when to choose it over similar tools like 'meta_tags_analyzer' which might analyze broader meta tags. There's no explicit or implied usage guidance.
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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