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lsmman

io.github.lsmman/fetchive

Official
by lsmman

Archive a pile of links

archive_batch

Extract links from pasted text, skip already archived, pull YouTube transcripts, and prepare page payloads for archiving. Returns a batch ID for background processing.

Instructions

Parse every link out of pasted text (a KakaoTalk or Slack export, a bare list, anything), skip what is already archived, extract YouTube transcripts, and prepare a page payload for each one. Returns a batch ID immediately; extraction runs in the background. Poll get_batch_status.

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 indicate readOnlyHint false and destructiveHint false, but the description adds crucial async behavior: 'Returns a batch ID immediately; extraction runs in the background' and 'Poll get_batch_status'. It also discloses that already-archived links are skipped. No contradictions with annotations.

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 main action, and includes necessary follow-up instruction. Every clause adds value with no redundancy.

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?

Given the tool's simplicity (one input), an output schema, and async behavior, the description adequately covers input semantics, immediate output (batch ID), and next steps. It omits error cases and rate limits, but these are not critical for basic selection and invocation.

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 sole parameter 'text' has no schema description, but the description explains it as 'pasted text (a KakaoTalk or Slack export, a bare list, anything)' and specifies it as the source of links. This fully compensates for the lack of schema coverage, though it doesn't mention size limits or formatting.

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 specific verbs: 'Parse every link out of pasted text', 'skip what is already archived', 'extract YouTube transcripts', and 'prepare a page payload'. It clearly states the tool's purpose and distinguishes it from siblings like ingest_links by emphasizing batch processing and asynchronous behavior.

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?

The description provides clear usage context, listing example input types ('KakaoTalk or Slack export, a bare list, anything') and instructing to poll get_batch_status. However, it lacks explicit exclusions or alternative tool references, such as when to use ingest_links instead.

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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