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gianni1989

timepiece-mcp

by gianni1989

timepiece_list_issues

Read-onlyIdempotent

List time-in-status for Jira issues matching a JQL query. Returns a table showing duration per status for each issue.

Instructions

List time-in-status data for multiple Jira issues selected by JQL query.

Uses the Timepiece list API to fetch time-in-status for all issues matching the JQL filter. Results are presented as a table with one row per issue.

Args: params (ListIssuesInput): Validated input containing: - jql (str): JQL query to select issues - columns_by (str): Column grouping (default: statusDuration) - calendar (Optional[str]): Timepiece calendar ID or name - day_length (str): 'businessDays' or 'calendarDays' (default: businessDays) - view_format (str): 'days', 'hours', 'minutes', 'seconds' (default: days) - statuses (Optional[str]): Comma-separated status IDs to filter - page_size (int): Results per page (1-1000, default 100) - response_format (str): 'markdown' or 'json' (default: markdown)

Returns: str: Table of issues with time-in-status per status column.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false. The description adds that it uses the Timepiece list API, returns a table, and supports markdown/json, but does not significantly extend beyond annotations. No contradictions.

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 structured with Args/Returns sections and front-loaded with the main purpose. It is reasonably concise given the tool's complexity, though some parameter information repeats schema content.

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?

The description covers the core behavior (list via JQL, output table), return format (markdown/json), and key parameters. Annotations cover safety. While the output schema is not described, the description states the return type. Some details like pagination are implicit via page_size. Overall, it is complete for the tool's complexity.

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?

The input schema has detailed descriptions for each parameter (e.g., JQL examples, defaults, constraints). The description lists parameters but adds minimal new meaning beyond the schema. Schema description coverage is effectively 100%, so 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?

The description clearly specifies the verb ('List'), resource ('time-in-status data for multiple Jira issues'), and method ('selected by JQL query'). It distinguishes from sibling tools like timepiece_get_issue (single issue) and timepiece_aggregate (aggregated data).

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?

The description states when to use it (fetching time-in-status for multiple issues via JQL) and implies it's for multiple issues versus siblings. However, it lacks explicit exclusions or comparisons across siblings. The JQL parameter examples provide some usage guidance.

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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