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LiLBrain

LiLBrain

by MangoByteLabs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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lilbrain_read

Read source code by function name or file path with line range to navigate and understand codebase definitions.

Instructions

Read source code of a function (by name) or file region (by path + line range).

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": "lilbrain_read"
  }
}

Input Schema

NameRequiredDescriptionDefault
endNoEnd line (for file reads)
nameYesFunction name or file path
startNoStart line (for file reads)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It does disclose that the operation is a read and indicates what input modes are supported, which is meaningful. However, it does not explain behavior around ambiguous names, missing line ranges, or return format.

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?

This is a single, efficient sentence that front-loads the verb and resource and covers both supported modes without filler. Every word earns its place.

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?

Adequate for a simple read tool, but the two-mode design leaves a real ambiguity: start and end are optional in the schema, yet the description implies a file region requires both. There is also no output-schema and no guidance on what happens when reading a bare file path.

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 input schema already covers all three parameters with meaningful descriptions (name as function/path, start/end for file reads), so the description does not need to add much. The mode-level framing adds mild clarity but no new detail about defaults, formats, or edge cases.

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 states a specific verb ('read') and a specific resource ('source code') with two clear modes: function by name and file region by path plus line range. It is clear and self-contained, but it does not explicitly contrast itself with sibling tools such as lilbrain_function or lilbrain_overview.

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?

No when-to-use versus alternatives guidance is provided. The description implies reading raw source code is the use case, but it never states when this tool should be preferred over sibling tools or when it should be avoided.

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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