Skip to main content
Glama

Vee3

by io.github.Vee3io

meta-tools.report_bug

Report a bug, error, or anything that did not work as expected while using Vee3.

Use this when a capability fails unexpectedly, returns wrong data, or behaves inconsistently. Include what you tried, what happened, and any error output

Cost = 0 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
summaryYesShort title describing the issue.
descriptionYesDetailed explanation of what went wrong, what was expected, and steps to reproduce if known.
error_detailsNoRaw error message, stack trace, or API response that shows the failure.
related_capability_idNoMCP tool name or capability id involved in the issue, if applicable.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoSubmission status. Always "received" on success.
report_idNoUnique identifier for the submitted bug report.
created_atNoISO 8601 timestamp when the report was recorded.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / related_capability_id / description
      Previous value: -"Capability id involved in the issue, if applicable."New value: +"MCP tool name or capability id involved in the issue, if applicable."
  2. Added

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It adds useful context like 'Cost = 0 tokens' and instructs what to include, but it does not disclose side effects, data handling, or what happens after submission.

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 three sentences with the purpose front-loaded. Every sentence contributes: what it does, when to use it, and what to include. No wasted words.

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?

The tool is simple, and an output schema is present (per context signals), so the description doesn't need to explain return values. It gives sufficient context for an agent to know when and how to invoke it, and clearly differentiates from siblings like request_feature by nature.

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 baseline is 3. The main description adds a reminder to include what was tried and error output, but this largely duplicates the schema's descriptions for the 'description' and 'error_details' parameters, adding little new meaning.

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 opens with a specific verb 'Report' and resource 'bug, error, or anything that did not work as expected while using Vee3'. It clearly distinguishes this from sibling meta-tools like request_feature by focusing on failures rather than feature requests.

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?

Provides explicit when-to-use triggers: 'when a capability fails unexpectedly, returns wrong data, or behaves inconsistently.' It does not mention when-not-to-use or name alternatives, but the context is clear enough.

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

All Vee3 toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation5/5

Each tool has a distinct purpose, further clarified by group prefixes and clear descriptions. Within each group, tools perform different operations (e.g., domains.lookup vs. domains.whois vs. domains.rdap) with no ambiguity.

Naming Consistency5/5

All tools follow a consistent group.tool_name pattern using snake_case. The naming is predictable and uniformly applied across all groups.

Tool Count4/5

78 tools is high, but the server aggregates multiple distinct API domains (11 groups). Each group has a reasonable number of tools, typically under 10, with TikTok having 17. The count reflects breadth, not bloat.

Completeness5/5

Each domain's tool set covers the primary expected operations (e.g., search, details, reviews, metrics, user info). There are no obvious gaps for read-only analytical use; features like posting are likely out of scope.

Resources