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confluence_comment_audit

Audit inline comments on Confluence pages to detect anchor drift after text edits. Returns status, original vs current text, and suggested fix for drifted comments.

Instructions

Audit every inline comment on a Confluence page for anchor drift. Inline-comment anchors do NOT follow text edits: when the annotated text is rewritten, Confluence leaves the mark on whatever original characters survive, so comments end up torn across fragments, slid onto unrelated text, or dropped. This compares each comment's currently-anchored text against the reviewer's durable original highlight and returns YAML with a per-comment status (ok/torn/mark_lost/drifted), the original vs. current anchored text, and a suggested_new_anchor for drifted comments. Read-only — fix drift with confluence_comment_reanchor. Mirrors omni-dev atlassian confluence comment audit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesConfluence page ID.
Behavior5/5

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

With no annotations provided, the description fully bears the burden. It explains the core behavioral trait: inline anchors do not follow edits, leading to drift. It details the output fields (status, original vs current text, suggested_new_anchor) and declares read-only semantics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is information-dense and front-loaded with the main purpose. While it is somewhat long, every sentence adds value. Could be slightly more terse, but it's well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description explains the YAML output format with specific fields. It also mentions the read-only nature and the related sibling tool for fixing drift, making it complete for an agent to use.

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

Parameters3/5

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

Schema coverage is 100% (only one parameter 'id' with description 'Confluence page ID'). The description does not add extra meaning beyond the schema description, so baseline 3 is appropriate.

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 verb 'Audit' and the resource 'every inline comment on a Confluence page' with a specific purpose: checking for anchor drift. It distinguishes itself from sibling tools like `confluence_comment_reanchor` by focusing on detection rather than fixing.

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 context on when to use (to audit anchors) and names an alternative (`confluence_comment_reanchor`) for fixing drift. However, it doesn't explicitly state exclusion cases or when not to use it, but the read-only nature is clear.

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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