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Get Project Revision History

openl_repository_project_revisions
Read-onlyIdempotent

Retrieve commit history for a project in a repository. Filter results by branch, search term, or paginate through revisions.

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. Pass either the id or name from openl_list_repositories() — both are accepted (case-insensitive). Do not invent example values; call openl_list_repositories() first if not in context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (0-based, default: 0)
sizeNoPage size (default: 50, max: 200)
branchNoBranch name (optional, only if repository supports branches)
searchNoSearch term to filter revisions by commit message or author
techRevsNoInclude technical revisions (default: false)
repositoryYesRepository identifier. Pass either the 'id' or the 'name' field from openl_list_repositories() — the tool accepts both (and is case-insensitive). DO NOT invent values like 'Design Repository' or 'design-repo'; the actual names are typically short tokens (e.g. 'Design'). Always call openl_list_repositories() first if you don't already have the value in context.
projectNameYesProject name within the repository (e.g., 'InsuranceRules', 'AutoPremium', 'ClaimProcessing')
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?

The annotations already indicate read-only, idempotent, and open-world. The description adds behavioral context: it returns a list of revisions with specific fields, supports pagination and filtering, and explains the repository parameter flexibility. This adds value beyond the annotations without contradiction.

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 four sentences, each adding distinct value: the first states the purpose, the second details output, the third mentions features, and the fourth gives parameter guidance. No fluff, well front-loaded.

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?

For 8 parameters (2 required) and no output schema, the description covers the key aspects: output content, pagination, filtering, and parameter sourcing. It could elaborate more on page/size defaults, but the schema already handles those. Overall, it is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds considerable meaning: it explains the repository parameter with concrete guidance (use values from openl_list_repositories(), case-insensitive), provides example project names, and describes the response_format enum options. This surpasses the bare 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 the tool gets revision history (commit history) of a project, listing commits with hashes, authors, timestamps, and types. This is a specific verb+resource that is distinct from sibling tools like openl_list_projects or openl_get_project.

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 provides explicit guidance on how to obtain the repository identifier using openl_list_repositories(), warns against inventing values, and explains the case-insensitivity. It also mentions pagination and filtering capabilities. However, it does not explicitly compare to sibling tools or state when not to use this tool.

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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