Geond Agent Protocol

Get symbol conflicts

get_symbol_conflicts

Check active symbol reservations that may conflict with your planned API or entity changes. Use before modifying shared interfaces to avoid collisions.

Instructions

Purpose: Read active symbol reservations that could conflict with planned work. When to use: call before changing shared APIs or named entities. Inputs: workspace_id and optional symbols filter. Side effects: none beyond database reads. Output: active symbol reservations with owners, purposes, and expiry. Failure modes: returns an empty list when there are no active conflicts.

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": {
      "workspace_id": "<workspace_id>"
    },
    "name": "get_symbol_conflicts"
  }
}

Input Schema

Name	Required	Description	Default
`symbols`	No	Optional symbol names or qualified identifiers to filter conflicts.
`workspace_id`	Yes	Workspace UUID whose symbol reservations should be checked.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 3, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Despite no annotations, the description fully discloses side effects ('none beyond database reads'), failure modes ('returns empty list when no active conflicts'), and output fields. This provides comprehensive behavioral insight beyond what annotations would cover.

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 structured into labelled sections (Purpose, When to use, Inputs, Side effects, Output, Failure modes) with no redundant sentences. Every element serves a clear purpose.

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's simple nature (2 params, read-only), the description covers all essential aspects: purpose, usage context, inputs, side effects, output, and failure modes. It is fully sufficient for an agent to use correctly, even without annotations or full output schema visibility.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, but the description adds value by summarizing the parameters and specifying output fields (owners, purposes, expiry). This enhances understanding beyond raw schema definitions.

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 specific verb ('Read') and resource ('symbol reservations that could conflict with planned work'), clearly distinguishing this read operation from sibling tools like get_active_reservations (all reservations) and reserve_symbols (creation).

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

Usage Guidelines4/5

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

Explicitly states 'call before changing shared APIs or named entities', providing a concrete usage scenario. Although it doesn't list explicit alternatives or exclusions, the context is clear enough for an agent to infer when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.