Skip to main content
Glama

confluence_history

List version history metadata for Confluence pages including version number, timestamp, author ID, and edit message. Filter by version number or date. Does not fetch page content.

Instructions

List version history (metadata only) for a Confluence page. Returns version number, timestamp, author account ID, edit message, and minor-edit flag for each version, newest-first. Does NOT fetch version bodies — use confluence_read for content. since filters to versions at or after a numeric version ("5") or ISO 8601 date ("2026-01-01T00:00:00Z"). limit defaults to 20; 0 means unlimited. Mirrors omni-dev atlassian confluence history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesConfluence page ID.
limitNoMaximum number of versions to return. `0` means unlimited. Defaults to 20.
sinceNoFilter to versions at or after this point. Accepts a numeric version number (e.g. `"5"`) or an ISO 8601 date (e.g. `"2026-01-01T00:00:00Z"`).
Behavior4/5

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

With no annotations, the description carries full burden. It discloses that only metadata is returned (not bodies), specifies return fields, and describes filter/limit behavior. It implicitly indicates read-only nature but doesn't explicitly state non-destructiveness. Minor gap, but overall transparent.

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 two sentences with no wasted words. First sentence sets purpose and returns list; second sentence packs filter/limit details and a CLI reference. Efficient and 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 a simple list tool with 3 fully described parameters and no output schema, the description covers purpose, returned fields, filtering, and limit. It lacks mention of error handling or pagination beyond limit, but is largely complete.

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%, so baseline is 3. The description adds context: explains 'since' accepts version number or ISO 8601 date, clarifies limit default and meaning of 0. This adds value beyond schema, earning a 4.

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 'List version history (metadata only) for a Confluence page' and lists specific returned fields. It distinguishes itself from sibling 'confluence_read' by explicitly noting it does not fetch version bodies, making the purpose unambiguous.

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?

The description explains when to use (for metadata) and when not (for bodies, directing to 'confluence_read'). It details filtering options ('since' accepts version number or date) and limit behavior (default 20, 0 unlimited), providing clear context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rust-works/omni-dev'

If you have feedback or need assistance with the MCP directory API, please join our Discord server