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lsmman

io.github.lsmman/fetchive

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by lsmman

Extract links from text

ingest_links
Read-onlyIdempotent

Extract all URLs from any text and classify them by platform to preview discovered links before saving.

Instructions

Pull every URL out of a text blob and classify it by platform, without archiving anything. Useful for showing the user what was found first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare read-only and idempotent hints, so the description adds value by disclosing platform classification and the no-archive behavior. It does not contradict annotations and provides additional context without needing deeper details.

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 two sentences, front-loaded with the core action, and contains no wasted words. Every clause adds information.

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

Completeness4/5

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

For a simple single-parameter extraction tool with a rich output schema and strong annotations, the description is mostly complete. It could specify the set of platforms considered, but the output schema likely covers that.

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

Parameters4/5

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

The schema has no description on the 'text' parameter (0% coverage), but the description's 'text blob' directly maps to the parameter's purpose. It is clear enough for an agent to know that the input should be the text to extract links from.

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 uses a specific verb ('Pull every URL out') plus resource ('text blob') and adds the classification behavior, which distinguishes it from siblings like archive_batch and extract_youtube_script. The phrase 'without archiving anything' also clarifies its scope.

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

Usage Guidelines4/5

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

It provides clear context ('Useful for showing the user what was found first') and an implicit exclusion ('without archiving anything'), but it does not explicitly name alternative tools or define when not to use this tool.

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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