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RepoChatMCP

RepoChatMCP

by gzmagyari
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

chat.read_knowledge_batch

Retrieve a specific page of text from a knowledge batch artifact using its batch ID, with offset and limit controls.

Instructions

Read paginated text from a specific persisted knowledge batch artifact.

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": {
      "batchId": "<batchId>"
    },
    "name": "chat.read_knowledge_batch"
  }
}

Input Schema

NameRequiredDescriptionDefault
kindNocombined, knowledge, or content_summary
limitNoMax lines to return (default 200, max 300)
offsetNo0-based line offset
batchIdYesKnowledge batch ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.11

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. It only states 'paginated text' and 'persisted', but fails to mention default limits, offset semantics, error behavior, or return format beyond plain text. This adds marginal value beyond the tool name.

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?

A single, front-loaded sentence that gets straight to the point with no extraneous information. Every word is useful.

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?

The description is adequate for a read operation with a well-documented schema, but without an output schema or annotations it leaves gaps about return structure and usage context. It is missing when-to-use guidance relative to sibling tools.

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%, with each parameter (kind, limit, offset, batchId) already described. The description itself adds no additional parameter context or examples, so it stays at the baseline.

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 uses a specific verb ('read') and resource ('persisted knowledge batch artifact'), and 'paginated text' clarifies the output format. It clearly distinguishes from sibling tools like list_knowledge_batches or read_latest_knowledge.

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 explicit guidance on when to use this tool versus alternatives. It does not mention read_knowledge_file, read_latest_knowledge, or search_knowledge, and only implies usage through the schema-required batchId parameter.

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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