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imdeniil

ya-tracker-mcp

by imdeniil

bulk_list_links

Fetch links for multiple issues in one parallel call, returning a compact structure. Use it for bulk operations like 'my tasks' where you need link data for many issues at once.

Instructions

Fetch links for multiple issues in a single call (parallel fan-out).

Use this instead of calling list_links N times — returns one compact structure instead of N separate tool result blocks. Ideal for flows like "my tasks" where you need links for many issues at once.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
compactNoIf True (default), each link is reduced to {key, display, type, direction, status} — cuts ~70% of bytes vs full objects. Set False to get raw API objects.
issue_keysYesList of issue keys (e.g. ["DEV-1", "DEV-2", "DEV-3"])
link_typesNoOptional filter by link type id (e.g. ["subtask", "relates", "depends on"]). If None, returns all link types.
output_formatNo"text" (default, grouped markdown) or "json" (structured).text
include_closedNoIf False, exclude links whose target issue has a resolution. Default: True.
max_concurrencyNoMax parallel API requests. Default: 10.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the parallel fan-out behavior and the compact combined result structure. However, it does not mention potential rate limiting, failure behavior, or whether the operation is read-only (though 'fetch' implies that). It provides some behavioral context but not comprehensive coverage.

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 short sentences, front-loaded with the purpose, then usage context. Every sentence earns its place; no filler.

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?

The tool has 6 parameters and an output schema, and the description covers the primary use case, differentiates from list_links, and provides an example. The output schema handles return value expectations. The only minor gap is not explaining the 'compact' parameter's impact on output, but that is covered in the schema.

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 description does not add any parameter-specific meaning beyond the schema, but the schema itself thoroughly documents each parameter. No further compensation needed.

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 begins with a specific verb ('Fetch') and resource ('links'), and clearly states the scope ('multiple issues in a single call'). It also distinguishes from the sibling tool list_links by noting it avoids N separate calls, which provides sibling differentiation.

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 states 'Use this instead of calling list_links N times' and gives an ideal use case ('my tasks' flows). This gives clear when-to-use guidance, though it doesn't explicitly say when not to use (e.g., for single issues), but the implication 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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