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Openl List Design Repository Project Revisions

openl_repository_project_revisions
Read-onlyIdempotent

Retrieve revision history of a project in a design repository, including commit hashes, authors, and timestamps. Supports filtering by branch and search term, with paginated results.

Instructions

Get revision history (commit history) of a project in a design repository. Returns list of revisions with commit hashes, authors, timestamps, and commit types. Supports pagination and filtering by branch and search term. Use repository name (not ID) - e.g., 'Design Repository' instead of 'design-repo'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repositoryYesRepository name (display name, not ID). Use the 'name' field from openl_list_repositories() response (e.g., if list_repositories returns {id: 'design-repo', name: 'Design Repository'}, use 'Design Repository' here, NOT 'design-repo').
projectNameYesProject name within the repository (e.g., 'InsuranceRules', 'AutoPremium', 'ClaimProcessing')
branchNoBranch name (optional, only if repository supports branches)
searchNoSearch term to filter revisions by commit message or author
techRevsNoInclude technical revisions (default: false)
pageNoPage number (0-based, default: 0)
sizeNoPage size (default: 50, max: 200)
response_formatNoResponse format: 'json' for structured data, 'markdown' for human-readable (default), 'markdown_concise' for brief summary (1-2 paragraphs), 'markdown_detailed' for full details with contextmarkdown
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the description's role is lighter. It adds context by listing return fields and clarifying repository usage, which enhances transparency beyond the annotations.

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?

Extremely concise: three sentences clearly state purpose, return content, and key usage note. Every sentence adds essential information with no redundancy.

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?

Given 8 parameters, no output schema, and complete annotation coverage, the description covers purpose, key behaviors, and parameter nuances. It could be more specific about return format details, but it sufficiently fills gaps.

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 detailed descriptions. The description reinforces critical parameter behavior (repository name format) and provides usage examples, 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?

The description clearly states it returns revision history (commit history) with specific fields like commit hashes, authors, and timestamps. It distinguishes itself from sibling tools, none of which focus on revision history.

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?

Explicitly instructs to use repository display name rather than ID, and mentions support for pagination and filtering. Lacks explicit exclusions or alternatives, but the guidance is clear and actionable.

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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