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frontmatter

Generate correctly-formatted frontmatter for static site generators and publishing platforms using article title and content, supporting Hugo, Jekyll, Astro, Next.js, Dev.to, Hashnode, and Ghost.

Instructions

Generate correctly-formatted frontmatter for any SSG or publishing platform (Hugo, Jekyll, Astro, Next.js, Dev.to, Hashnode, Ghost) — FREE

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesThe article title
contentYesThe article content — used to auto-extract description, reading time, tags
formatYesTarget frontmatter format
tagsNoOptional tags — auto-extracted from content if omitted
canonical_urlNoCanonical URL for the article
featured_imageNoFeatured/cover image URL
authorNoAuthor name
draftNoWhether the post is a draft (default: true)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool generates frontmatter but omits critical details: whether this is a read-only or mutating operation, any rate limits, authentication needs, or what the output format looks like. The mention 'FREE' hints at no cost but doesn't clarify other behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Generate correctly-formatted frontmatter') and includes essential context (platforms, free). There is zero wasted text, making it highly concise and well-structured for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (8 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, output format, error handling, or how it integrates with sibling tools. Without annotations or an output schema, the description should compensate more to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the schema already documents all 8 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as explaining interactions between parameters (e.g., how 'content' auto-extracts data). Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Generate correctly-formatted frontmatter') and the target resources ('any SSG or publishing platform'), with explicit examples listed. It distinguishes itself from sibling tools by focusing exclusively on frontmatter generation, unlike tools for posting, auditing, or SEO analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by mentioning target platforms (e.g., Hugo, Jekyll) and notes it's 'FREE', but provides no explicit guidance on when to use this tool versus alternatives like 'seo_meta' or 'save_draft'. It lacks clear when-not-to-use criteria or prerequisites, leaving usage somewhat ambiguous.

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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