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transmission-mcp

Reannounce Torrent to Trackers

transmission_reannounce_torrent

Force torrents to reannounce to trackers, updating peer lists and fixing connection issues. Specify torrent IDs or 'all' to trigger an immediate announce.

Instructions

Force torrent(s) to reannounce to their trackers.

This tool forces an immediate announcement to trackers, which can help update peer lists or fix connection issues. Normally, Transmission announces automatically at regular intervals.

Args:

  • ids (number | number[] | 'all'): Torrent ID(s) to reannounce

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

Returns: Confirmation that reannounce request was sent

Examples:

  • Use when: "Update tracker for torrent 5"

  • Use when: "Not getting any peers, force an announce"

  • Use when: "Reannounce all torrents" -> params with ids='all'

Error Handling:

  • Returns error if torrent IDs don't exist

  • Success doesn't guarantee tracker response (depends on tracker availability)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYesTorrent ID(s) to operate on - can be a single ID, array of IDs, or 'all'
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown
Behavior4/5

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

The description adds value beyond annotations by explaining that success does not guarantee tracker response and that it forces an immediate announcement versus the normal automatic interval. It also covers error handling for invalid torrent IDs. 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.

Conciseness4/5

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

The description is well-structured with sections for purpose, args, returns, examples, and error handling. It is front-loaded with the main action and uses bullet points for examples. While slightly longer than necessary, every sentence adds value.

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

Completeness5/5

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

Given the tool's simplicity (2 params, no output schema, good annotations), the description covers all necessary aspects: purpose, usage scenarios, parameter details, error handling, and behavioral limitations. It is complete for an AI agent to correctly invoke the tool.

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?

Schema coverage is 100%, so the description's parameter info (ids and response_format) is redundant but provides useful examples. It adds context for the ids parameter accepting various formats and response_format default. Baseline of 3 is appropriate as the schema already defines the parameters well.

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's action: 'Force torrent(s) to reannounce to their trackers.' It uses a specific verb (reannounce) and resource (torrents to trackers), distinguishing it from sibling tools like transmission_add_torrent or transmission_pause_torrent.

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 explicit use cases such as 'update peer lists', 'fix connection issues', and gives examples like 'Not getting any peers, force an announce'. It does not explicitly state when not to use, but the context is sufficient for an AI agent to understand appropriate scenarios.

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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