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List Tracker bulk-change failed issues

tracker_bulk_issues_list
Read-onlyIdempotent

List issues a bulk-change operation could not change, with per-field errors, to diagnose why specific issues were rejected after bulk_get reports failures.

Instructions

The issues a bulk-change operation could NOT change, each with its per-field error.

Use after bulk_get reports a non-zero failure count to see why specific issues were rejected (e.g. an invalid resolution for the target queue/type). Successful issues are not listed here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bulk_idYesBulk-change operation id to inspect.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.67.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, so the safety profile is covered. The description adds real value beyond that by disclosing the return content (per-field error per failed issue) and the exclusion of successful issues. It does not cover pagination or auth, keeping it short of a 5.

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?

Two tight sentences, front-loaded with the core definition, then the usage trigger and exclusion. Every clause earns its place.

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?

With no output schema, the description usefully explains what the returned records contain (per-field errors). Combined with annotations covering safety, an agent has enough to call it correctly; only pagination/ordering behavior is unspecified.

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% for the single bulk_id parameter, so the schema already documents it. The description reinforces that the id refers to a bulk-change operation but adds no syntax or format detail beyond the schema. Baseline 3 applies.

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?

States a specific verb and resource ('issues a bulk-change operation could NOT change'), and adds the distinguishing scope detail that successful issues are excluded. This clearly separates it from tracker_bulk_get and other list siblings.

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

Usage Guidelines5/5

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

Explicitly names the trigger condition ('after bulk_get reports a non-zero failure count') and the alternative tool, plus the intended purpose (see why specific issues were rejected). An agent needs no inference to know when to call this.

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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