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confluence_read

Read a Confluence page by ID as markdown (default) or ADF JSON. For large pages, write to file and get a summary to save context space.

Instructions

Fetch a Confluence page by ID. Returns JFM markdown by default, or raw ADF JSON when format="adf". When output_file is set, the content is written to that path and the tool returns a short YAML summary (path/bytes/format) — useful for large pages. Mirrors omni-dev atlassian confluence read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoOutput format: `"jfm"` (default, AI-friendly markdown) or `"adf"` (raw ADF JSON).
idYesConfluence page ID (e.g., "12345678").
output_fileNoWhen set, writes the rendered content to this path and returns a short YAML summary (path/bytes/format) instead of the inline body. Useful for large pages that would otherwise blow past the context window — the assistant can then read the file with offset/limit.
Behavior3/5

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

No annotations are provided, so the description must carry the behavioral burden. It discloses that output_file changes behavior to return a YAML summary instead of inline body, and that JFM is the default format. However, it does not explicitly state that the tool is read-only, non-destructive, or that it may require authentication or handle errors, though these are implied by the verb 'Fetch'.

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?

Three concise sentences with zero fluff. The first sentence immediately states the tool's purpose. Subsequent sentences logically elaborate on format options and file output. Every sentence earns its place.

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 read tool without an output schema, the description covers the key behaviors: return format, file output use case. It does not detail error handling or pagination, but given the low complexity and the presence of sibling tools for search/children, this is adequate.

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 value beyond the schema: it clarifies the default format (JFM) and explains that output_file is useful to avoid context window limits, enabling the assistant to then read the file. This provides practical guidance not present in the blank schema descriptions.

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 "Fetch a Confluence page by ID." It distinguishes from sibling tools like confluence_create (write) and confluence_search (lookup) by specifying the action as fetching a single page by ID. The mention of JFM markdown and ADF JSON further clarifies the output.

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 explains when to use the output_file parameter (for large pages) and the format parameter (JFM vs ADF). However, it does not explicitly compare to alternatives like confluence_children or confluence_search for when reading a specific page is preferable, though this is implied.

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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