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SignalPipe

by io.github.AbYousef739
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list_stations

Read-onlyIdempotent

List your stations (feeds) with a health readout for the last two weeks.

Each station: id, name, platform, rss_url, read_by (server = SignalPipe
reads it, client = your plugin or daemon reads it), active, posts captured,
how many reached your queue, empty or rate-limited fetches, and a
plain-language verdict (for example "Posts are arriving but none matched
your product: change the anchor sentences").

Presentation: one line per station with name, active or paused, and the
verdict. Use the ids with update_station / remove_station.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_stations"
  }
}

Input Schema

NameRequiredDescriptionDefault
product_idNoOptional. Only this product's stations; leave empty for all of them.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / product_id / description
      Added value: +"Optional. Only this product's stations; leave empty for all of them."
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already establish the safety profile (readOnly, idempotent, non-destructive), and the description adds real behavioral context beyond them: the exact fields returned, the meaning of read_by (server vs client reader), counters like posts captured vs queued vs rate-limited, and a plain-language verdict. It stops short of stating pagination or auth requirements, so it is not fully exhaustive.

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?

Front-loaded with the purpose and scope, then a structured field inventory and presentation note. Efficient overall, though the verdict example is slightly verbose and the description runs long for a list tool.

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?

There is no output schema, so the description correctly carries the full burden of describing the returned fields, their meaning, and the rendered presentation. An agent has everything needed to call it and interpret the result.

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% and the single product_id parameter is already documented in the schema, so the description need not carry parameter burden. It adds no syntax or format detail beyond the schema, making the baseline 3 correct.

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?

States a specific verb and resource ("List your stations (feeds)") plus a defined scope ("health readout for the last two weeks"). It also distinguishes itself from the mutating siblings by telling the agent to feed the returned ids into update_station/remove_station.

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?

Usage is implied rather than stated: the agent learns the ids feed update_station/remove_station, and product_id filters the scope, but there is no explicit when-to-use/when-not guidance versus siblings like preview_station or get_pipeline. Adequate but leaves the alternative selection to inference.

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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