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Linear

by io.github.pipeworx-io

Linear Create Issue

linear_create_issue
Idempotent

Create a new issue in Linear with title and optional description. Returns issue ID, key, title, and URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesIssue title
teamIdYesTeam ID to create the issue in
priorityNoPriority level: 0 (none), 1 (urgent), 2 (high), 3 (medium), 4 (low)
descriptionNoIssue description (markdown supported)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
issueNo
successYesWhether issue creation succeeded

TDQS

A3.5/5.0
Behavior2/5

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

Annotations declare readOnlyHint=false, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description does not add behavioral context beyond stating 'create'. It does not mention idempotency, side effects, or any constraints not already in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the purpose. It is concise but could benefit from a clearer separation of input and output.

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?

Includes return values and mentions optional description. Given the presence of an output schema and 100% parameter coverage, the description is fairly complete. However, lacks siblings differentiation and usage context.

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 coverage is 100% with descriptions for all 4 parameters. The description mentions 'title' and 'optional description' but does not add meaning beyond the schema for teamId or priority. Baseline score of 3 applies due to high coverage.

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 clearly states the verb 'create', the resource 'new issue in Linear', and the return values (issue ID, key, title, URL). This distinguishes it from sibling tools like linear_get_issue or 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 Guidelines3/5

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

The description implies usage for creating issues but provides no explicit guidance on when to use this tool versus alternatives like linear_search or linear_get_issue. No when-not-to-use information is provided.

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