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list_issues

Read-onlyIdempotent

Fetch every Linear ticket matching filters in one call, paging through all results. Returns totals, state counts, and rows for each issue; narrow filters if over 2000 matches.

Instructions

Every ticket matching the filters, in one call: the server pages through Linear to the end, so the answer is the whole set (total, by_state, and one row per ticket under columns). Rows hold identifier, title, state, assignee, delegate and updatedAt; there are no description excerpts, so read a ticket with get_issue before acting on it. More than 2000 matches is refused; narrow with open, state, cycle, project, assignee_is_me or delegate_is_me. When a task covers a set, work every row.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
openNoOnly tickets not in a completed or canceled state
teamNoTeam key, e.g. ENG
cycleNoCycle number within team (list_cycles gives them); needs team
queryNoFull-text search term. Omit to list by most recently updated.
stateNoWorkflow state name, e.g. "In Progress"
projectNoProject name or id
assignee_is_meNo
delegate_is_meNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNoOne array per ticket: identifier, title, state, assignee, delegate, updatedAt; no descriptions
totalNoHow many tickets match; rows holds every one of them
columnsNoNames of the values in each row, in order
by_stateNoCount of matching tickets per workflow state
completeNoAlways true: a partial set is refused, never returned

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations cover the safety profile, but the description adds substantial non-obvious behavior: server-side pagination to completion, a hard refusal above 2000 matches, and the exact row columns returned. These are operational traits the annotations cannot express.

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 dense sentences, front-loaded with scope, then return shape, then constraints and routing. No filler; every clause carries information (cap, pagination, columns, alternative tool).

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?

Even though an output schema exists, the description clarifies what the rows actually contain and the failure mode at 2000 matches. Combined with annotations and schema, an agent has everything needed to call and interpret this tool correctly.

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 75%, so the schema already documents most params. The description enumerates the narrowing filters, which adds modest signal about which params constrain the result set, but does not add format or syntax detail beyond the schema. Baseline 3 is appropriate.

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+resource ('Every ticket matching the filters, in one call') and distinguishes itself from get_issue by noting rows hold no description excerpts. An agent can tell what it returns and how it differs from the sibling detail tool without opening the schema.

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 routes the agent: 'read a ticket with get_issue before acting on it', and 'narrow with open, state, cycle, project, assignee_is_me or delegate_is_me' when matches exceed 2000. Also names the use case 'when a task covers a set, work every row'. Covers when-to-use, when-not (too broad), and the alternative.

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