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by JustinA988
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

read_source

Read-only

Read a capped slice from a configured source by name, using path, JSON pointer, offset, and limit to retrieve only the needed characters or rows.

Instructions

Read a capped slice of a configured source. pointer is a JSON pointer.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

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

Input Schema

NameRequiredDescriptionDefault
nameYesSource name.
pathNoFile inside a directory source.
limitNoMax characters or rows.
offsetNoCharacter or row offset.
pointerNoJSON pointer.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

The annotations already declare this is a safe, read-only, non-destructive, closed-world operation. The description adds that reads are capped to a slice, which is useful behavioral context, but it does not explain cap size, defaults, offset/limit interactions, source-name discovery, or error behavior.

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 short and front-loads the core operation, with no wasted introductory material. The second sentence is largely redundant with the schema, but the overall definition remains tight.

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

Completeness3/5

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

Annotations and the fully documented input schema carry most of the burden, and the description states the bounded-read behavior. However, for a five-parameter tool with no output schema, it does not explain source types, how source names are discovered, or how path and pointer selection works.

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 description coverage is 100%, so the schema already documents all five parameters. The description's only parameter note, 'pointer is a JSON pointer,' repeats the schema text and adds no new semantics for name, path, limit, or offset.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Read') and names the resource ('a configured source') with a scope qualifier ('capped slice'). It is clear enough to understand the operation, but 'configured source' is not defined and there is no explicit differentiation from the sibling read_file or query_sql tools.

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

Usage Guidelines2/5

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

The description gives no explicit when-to-use guidance, no when-not-to-use conditions, and no alternatives. An agent is left to infer that this tool is for configured sources rather than direct files or SQL queries.

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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