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get_sources

Returns all published Arco sources for a term — Lexicon entries, blog articles, wiki pages, and podcast episodes — ordered by recommended reading sequence. Read-only. Use this when you need a reading list or reference list for a term. Use cite_term instead when you need a formatted citation for a specific publication type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
termYesThe Lexicon term whose sources to retrieve. Accepts canonical name or slug.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / term / description
      Added value: +"The Lexicon term whose sources to retrieve. Accepts canonical name or slug."
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It explicitly states 'Read-only,' discloses the ordering ('ordered by recommended reading sequence'), and restricts to 'published' sources. It doesn't detail error handling or edge cases, but for a read-only list retrieval, this is sufficient. Slightly more detail on empty results or invalid terms would push to a 5.

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 concise and front-loaded: the first sentence states the core functionality and scope, the second adds the read-only nature and usage context, and the third names the alternative tool. Every sentence carries essential information without redundancy or padding.

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 has a single parameter, no output schema, and no annotations, the description covers all necessary context: what sources are returned, their ordering, that it's read-only, when to use it, and when to use the alternative. The tool is simple enough that this is complete for correct agent invocation.

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?

The schema provides 100% parameter coverage with a clear description of the `term` parameter, including that it accepts canonical name or slug. The tool description does not add extra parameter-level semantics beyond that, so the baseline of 3 is appropriate given the schema already fully documents the parameter.

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 all published Arco sources for a term, listing specific source types (Lexicon entries, blog articles, wiki pages, podcast episodes) and notes the ordering by recommended reading sequence. It also distinguishes itself from the sibling tool cite_term, making its purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly instructs when to use this tool: 'Use this when you need a reading list or reference list for a term.' It also provides a clear alternative: 'Use cite_term instead when you need a formatted citation for a specific publication type.' This gives the agent both positive and negative usage guidance.

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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