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get_post_content

Retrieve a post's full body or free preview based on your access. Optionally convert HTML to Markdown for LLM processing.

Instructions

Read-only. Return a post's body. Auth-aware: returns full text for paywalled posts you have access to, otherwise only the free preview. Set as_markdown=true to convert HTML to Markdown for LLM context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
post_idYes
pubNo
as_markdownNo
Behavior4/5

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

With no annotations, the description carries full burden. It discloses read-only behavior and auth-aware paywall handling, adding significant context. However, it omits details like rate limits, error handling, or side effects.

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?

Three concise sentences, front-loaded with key action. No unnecessary words. Every sentence adds value: first sets context, second adds nuance, third adds optional parameter guidance.

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

Completeness3/5

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

Given no output schema and 3 parameters, the description covers core purpose and auth behavior but not return format or error states. It partially compensates for missing annotations but could be more explicit about output structure.

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

Parameters2/5

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

Schema coverage is 0%, so description must compensate. It only explains as_markdown (conversion to Markdown for LLM). Post_id and pub parameters are not described, leaving the agent guessing their purpose or format.

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 tool returns a post's body, and specifies read-only nature with auth-aware behavior. It distinguishes from siblings like get_post by focusing on content body rather than metadata.

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 this tool is for fetching post body content, but does not explicitly state when to use it over alternatives like get_post or search_posts. No usage exclusions are provided, and siblings are not referenced.

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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