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List saved queries

list_queries
Read-onlyIdempotent

List saved OpenProject work-package views (queries) for the current user, enabling discovery of existing team boards and filters before building custom ones.

Instructions

List the saved work-package views (queries) this user can open.

Use it to discover what a team already tracks — "Sprint board", "My open bugs", "Overdue in Platform" — before hand-building filters: running someone's saved view with run_query reproduces exactly what they see in the UI, including their grouping and sums.

Returns the standard list envelope: rows of {id, name, project, public, starred, updated_at} plus pagination. project is null for a global query (saved outside any project); public false means the query is private to its owner, and only the owner's queries are visible to this account.

Pitfalls. Query ids are instance-wide, not per project — never guess one, take it from here. This lists definitions only; it never runs them, so nothing here says how many work packages a query returns.

Cross-references: run one with run_query(query_id=…); build an ad-hoc query instead with list_work_packages; project ids come from list_projects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-based page number.
page_sizeNoQueries per page (max 100).
project_idNoNumeric project id to list only that project's saved views. Comes from list_projects. Omit to list everything visible to the current user, global queries included. A project identifier (URL slug) is not accepted here by OpenProject — use the numeric id.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sumsNoPresent only when show_sums was requested.
itemsNoThe page of results.
notesNoDegradation markers: capped aggregations, unavailable modules, …
groupsNoPresent only when group_by was requested.
paginationYesTotal/page/page_size/has_more.
Behavior5/5

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

Beyond annotations (readOnlyHint, openWorldHint, idempotentHint), the description discloses the return envelope shape, null semantics for project, public/private visibility, instance-wide query IDs, and the fact that it never runs queries—so it cannot reveal result counts. This is rich behavioral context that helps the agent understand side effects and limitations.

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?

The description is well organized into purpose, usage guidance, return details, pitfalls, and cross-references. Every sentence contributes valuable information without redundancy, and the main verb and object lead the first sentence, making it front-loaded and easy to scan.

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 the presence of an output schema, the description still explains the envelope and important edge cases such as global queries, visibility rules, and ID scope. It also covers cross-tool relationships with run_query, list_work_packages, and list_projects, leaving no obvious gaps for an agent to misuse the tool.

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 already provides thorough descriptions for all three parameters, including project_id's numeric requirement, default behavior, and relationship to list_projects. The description adds little parameter-level meaning beyond what the schema offers, so baseline 3 applies with 100% schema 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 opens with 'List the saved work-package views (queries) this user can open,' which clearly identifies the action and resource. It distinguishes itself from siblings like run_query and list_work_packages by explicitly focusing on saved definitions rather than executing or building queries.

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

Usage Guidelines5/5

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

It explicitly advises using this tool to discover what a team already tracks before hand-building filters, and it names alternatives: 'run one with run_query(query_id=…)', 'build an ad-hoc query instead with list_work_packages', and 'project ids come from list_projects'. This provides clear when-to-use and alternative 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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