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organisation.md

organisation.md

by shashank-sn
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

add_info

Adds information to a GitHub-based knowledge base using natural language. Automatically determines the correct section and file for the input.

Instructions

add information to the knowledge base using natural language. describes what to add, and the tool figures out which section and file to put it in.

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": {
      "info": "<info>"
    },
    "name": "add_info"
  }
}

Input Schema

NameRequiredDescriptionDefault
infoYesthe information to add, in natural language (e.g., 'our new project is called veridian, led by alice, focused on data pipelines')
sourceNooptional source reference (e.g., 'meeting notes 2025-06-20', 'slack thread')
sectionNospecific section to add to (auto-detected if omitted)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are present, so the description carries behavioral disclosure. It states the tool 'figures out which section and file to put it in', which adds context about automatic placement. However, it does not discuss side effects, permissions, or whether it overwrites or appends.

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 extremely concise with two sentences. It immediately states the purpose and key behavior, with no unnecessary words.

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 tool modifies the knowledge base, but the description omits what the tool returns, error handling, or permission requirements. While the basic use case is covered, a modification tool typically needs more context for safe usage.

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 described. The overall description reinforces the 'natural language' aspect and auto-detection for section, but does not add significant new meaning beyond the schema for individual params.

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's purpose: to add information to the knowledge base using natural language, and it specifies that the tool determines the appropriate section and file. This distinguishes it from sibling tools like update_section or remove_info.

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?

The description implies usage for adding natural language info, but does not explicitly mention when to use this tool versus alternatives like propose_change or import_file. No 'when not to use' guidance is provided.

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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