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Get Issue Fields

get_issue_fields
Read-onlyIdempotent

Retrieve valid field names for issue queries by inspecting a sample issue from your MantisBT server, ensuring you only request available fields.

Instructions

Return all field names that are valid for the "select" parameter of list_issues and get_issue.

Fields are discovered by fetching a sample issue from MantisBT (which reflects the server's active configuration — e.g. whether eta, projection, or profile fields are enabled) and merging the result with fields that MantisBT omits when empty (notes, attachments, relationships, etc.). The result is cached with the same TTL as the metadata cache.

Use this tool before constructing a "select" string to ensure you only request fields that exist on this server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idNoOptional project ID to scope the sample issue fetch
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, so the bar is lower. The description adds value by explaining the discovery mechanism (fetching sample issue, merging with omitted fields) and caching behavior with TTL, which are not covered by annotations.

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?

Three well-structured paragraphs: first sentence states purpose, second explains mechanism, third recommends usage. No filler or redundant information. Every sentence serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, but the description clearly states the return is field names. It covers the discovery mechanism, caching, and the recommendation to use before select. Some details (e.g., cache invalidation) are missing, but overall it's sufficiently complete for the tool's purpose.

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 coverage is 100% with a description for the only parameter (project_id). The tool description adds minimal extra context ('scope the sample issue fetch'), which aligns with the schema. Baseline 3 is appropriate since the schema already does the heavy lifting.

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 it returns valid field names for the 'select' parameter of two specific tools (list_issues, get_issue). This is a specific verb+resource, and it distinguishes itself from siblings like get_issue_enums or list_issues.

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?

It explicitly advises using this tool before constructing a 'select' string to ensure field existence. While it doesn't explicitly state when not to use it, the context implies it's a preparatory step, and the recommendation is clear.

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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