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GitHub + Linear Dev Workflows

GitHub + Linear Dev Workflows

by r28ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

linear_search_issues

Read-onlyIdempotent

Search Linear issues by text in titles, descriptions, and optionally comments. Use issues_list to filter by state, assignee, or other fields.

Instructions

Search issues by text, across titles and descriptions. Set include_comments to search inside comments too. This is full-text search; to filter on fields such as state or assignee, use issues_list.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "variables": "<variables>"
    },
    "name": "linear_search_issues"
  }
}

Input Schema

NameRequiredDescriptionDefault
variablesYesWhat to search for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so safety is covered. The description adds genuinely useful behavioral context beyond them: the search spans titles and descriptions, and comment text is only included when include_comments is set. No return-format or pagination detail, but the schema's `after`/`first` params cover that.

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 short sentences, front-loaded with what the tool does, then the one parameter worth calling out, then the routing rule. No filler and nothing buried.

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?

For a one-parameter, read-only search wrapper whose input schema documents every field, the description supplies exactly the missing layer: search scope, the include_comments toggle, and when to prefer the sibling. Nothing an agent needs in order to call it correctly is absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, and the description still adds real meaning: it defines the search surface (titles and descriptions) and explains the effect of include_comments rather than restating its schema text. It does not, however, reconcile that guidance with the presence of a `filter` object in the schema.

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?

Specific verb (search) plus resource (issues) plus the exact searchable fields (titles and descriptions). It explicitly names the sibling it is not (issues_list) and characterizes itself as full-text, so an agent can separate it from filter-based listing without opening either schema.

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 states the alternative and the selecting condition: use issues_list to filter on fields such as state or assignee. That is clear routing guidance, though it slightly undersells the tool's own `filter` parameter, which the schema shows can narrow results on top of the text match.

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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