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Linear

by io.github.pipeworx-io

Linear Get Issue

linear_get_issue
Read-onlyIdempotent

Get full details of a Linear issue by ID (e.g., "ABC-123"). Returns title, description, state, priority, assignee, labels, comments, and URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesIssue identifier (e.g., "ABC-123")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoIssue ID
urlNoIssue URL
stateNo
titleNoIssue title
labelsNo
assigneeNo
commentsNo
priorityNoPriority level
createdAtNoCreation timestamp
updatedAtNoLast update timestamp
identifierNoIssue identifier (e.g., ABC-123)
descriptionNoIssue description in markdown
priorityLabelNoHuman-readable priority label

TDQS

A3.7/5.0
Behavior2/5

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

Annotations already indicate readOnlyHint, idempotentHint, destructiveHint=false. Description adds no behavioral context beyond the return fields, and does not disclose auth requirements, rate limits, or side effects.

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?

Single sentence, 20 words, front-loaded with action and key details. No wasted words.

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?

Given an output schema exists, the description is fully adequate: it explains purpose, input format, and return contents. For a simple read tool with one parameter, it is complete.

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% with one parameter described as 'Issue identifier (e.g., "ABC-123")'. The description reinforces the format with an example, adding value beyond 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?

Description clearly states it gets full details of a Linear issue by ID, listing specific return fields (title, description, state, etc.). It distinguishes from sibling tools like linear_create_issue and linear_list_issues.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool vs alternatives like linear_search. The description implies use when you have an issue ID, but lacks exclusions or context for when not to use it.

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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TDQS

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, especially within their domains (e.g., Polymarket tools are well-separated). However, a few tools like ask_pipeworx, deep_research, and suggest_questions could cause minor confusion, as they all deal with querying data.

Naming Consistency3/5

Tools from the same service use consistent prefixes (linear_, polymarket_, pipeworx_), but the overall naming style is mixed: some are verb_noun (linear_create_issue), some are noun_verb (bet_research), and some are single words (remember). This inconsistency reduces predictability.

Tool Count3/5

With 35 tools, the server covers a broad range of functionality (data query, prediction markets, memory, etc.). While not excessive, the count is on the higher side, and the server name 'Linear' suggests a narrower focus, which may mislead expectations.

Completeness4/5

The tool set covers core data querying, research, entity profiles, prediction market analysis, and memory operations comprehensively. Minor gaps exist (e.g., limited Linear CRUD), but the overall surface feels complete for its intended use as a data assistant.

Resources