linear_get_issueFetch a single issue by its UUID or human identifier (e.g. "ENG-123"), including description, state, assignee and recent comments. Read-only. GraphQL: query issue(id).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Issue UUID or identifier like "ENG-123". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It declares 'Read-only' and mentions the underlying GraphQL query. However, it does not cover error handling, permissions, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences, front-loaded with the main action, and no unnecessary words. Every part adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-fetch tool with one parameter and no output schema, the description covers the return fields (description, state, assignee, comments) and the identifier format, providing sufficient context for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The tool description echoes this information without adding new meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action (fetch), resource (issue), and identifiers (UUID or human identifier). It distinguishes from siblings like linear_search_issues that perform searches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
States 'Read-only' and implies use when you have a specific ID, but does not explicitly mention when to use alternatives like linear_search_issues. Still clear for a single-fetch tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: adding comments, creating issues, fetching by ID, listing cycles/projects/teams, viewing assigned issues, and searching. No ambiguity between them.
All tools follow a 'linear_' prefix with verb_noun pattern (e.g., linear_create_issue, linear_list_teams). The exception is 'linear_my_issues' which is not strictly verb_noun but still intuitive.
With 8 tools, the set is well-scoped for a project management integration. It covers core operations without being overwhelming or sparse.
Covers basic CRUD for issues (create, get, comment) and listing of projects/cycles/teams, but missing update_issue and delete_issue, which are notable gaps for a complete workflow.