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hasanozcan

Azure DevOps MCP Server

by hasanozcan

Query work items

query_work_items

Run read-only WIQL queries to fetch matching Azure Boards work items and their details.

Instructions

Run a read-only WIQL SELECT query and resolve matching Azure Boards work item details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNoMaximum query results; defaults to 100.
wiqlYes
fieldsNoOptional Azure Boards field reference names, for example System.Title or System.Description.
projectNoProject name or ID. Uses AZURE_DEVOPS_DEFAULT_PROJECT when omitted.
timePrecisionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.7/5.0
Behavior3/5

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

Since no annotations are provided, the description carries the behavioral disclosure burden. It clearly discloses read-only intent and the fact that it resolves matching work item details, which is useful. However, it does not describe result count limits, default top behavior, field resolution behavior, or what happens when a query returns no matches, so significant behavioral context still remains.

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 a single, front-loaded sentence that packs the operation, the read-only safety signal, the query-language constraint, the resource, and the outcome into minimal text. Every part contributes, and there is no filler or repetition of the tool name.

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?

For a query tool with no output schema and no annotations, the description is a reasonable high-level summary but not fully complete. It omits any mention of result pagination, default result size, project defaulting behavior, or the nuanced timePrecision parameter, which an agent would need when constructing correct calls in edge cases.

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 60%, so wiql, fields, top, and project already have partial schema-level documentation. The description adds the WIQL SELECT context and the 'resolve details' behavior, but it does not explain timePrecision or otherwise compensate for the missing schema descriptions. This is adequate but not strongly additive.

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-resource pair, 'Run a read-only WIQL SELECT query' on Azure Boards work items, and adds the resolution step, making clear this is a query-time retrieval tool. It distinguishes itself from get_work_item and iteration work item tools by focusing on WIQL SELECT queries rather than ID-based or iteration-based lookups.

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 conveys the core use case — running a WIQL SELECT query and resolving work item details, so usage is implied rather than absent. However, it never explicitly states when to choose this over get_work_item, get_iteration_work_items, or other work-item retrieval tools, and gives no exclusions, leaving selection largely to inference.

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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