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atlassian_convert

Convert JIRA-Flavoured Markdown to Atlassian Document Format JSON or vice versa. Works offline with no credentials needed.

Instructions

Convert between JFM (JIRA-Flavoured Markdown) and ADF (Atlassian Document Format) JSON. Bidirectional and fully offline — performs no network I/O and needs no Atlassian credentials. Set direction to "to-adf" to convert JFM markdown into an ADF JSON document (e.g. # Title becomes {"version":1,"type":"doc","content":[...]}), or "from-adf" to render an ADF JSON document back into JFM markdown. Use it to preview or inspect the ADF a JIRA/Confluence write tool would send. Output is the converted document (JSON for to-adf, markdown for from-adf). Mirrors omni-dev atlassian convert to-adf / from-adf.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
compactNoWhen `direction = to-adf`, emit compact JSON instead of pretty-printed.
contentYesThe content to convert. For `to-adf` this is JFM markdown; for `from-adf` this is an ADF JSON document.
directionYesDirection of the conversion: `to-adf` (markdown → ADF JSON) or `from-adf` (ADF JSON → markdown).
strip_local_idsNoWhen `direction = from-adf`, strip `localId` attributes from output for better readability. For reading only — do NOT write stripped output back to Confluence, as `localId`s anchor inline comments and dropping them makes Confluence lose those comments.
Behavior4/5

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

With no annotations, the description discloses that the tool is bidirectional, fully offline, performs no network I/O, and needs no credentials. It also warns about the 'strip_local_ids' parameter's potential impact on Confluence comments, adding important behavioral context.

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 remarkably concise with no filler. Three sentences cover purpose, behavior, examples, and a critical warning. Front-loaded with the core purpose.

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 high schema coverage, no output schema, and no annotations, the description is adequately complete. It explains purpose, behavior, parameter usage, and even provides example output format for one direction. Lack of explicit output schema description is acceptable.

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%, baseline 3. The description adds value by giving conversion examples for 'direction' and explaining 'compact' and 'strip_local_ids' with usage warnings, beyond the schema's 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 states 'Convert between JFM and ADF JSON' with a specific verb and resource. It distinguishes from sibling tools by emphasizing offline, credential-free conversion, which no other tool offers.

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 advises using the tool to 'preview or inspect the ADF a JIRA/Confluence write tool would send' and highlights offline operation, giving clear context. It does not explicitly state when not to use or name alternatives, but the context is sufficient.

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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