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azamlerc

confluence-mcp-server

by azamlerc

confluence_parse_html

Parse raw HTML from a confluence.org point page to extract structured location data such as country, nearest place, and altitude.

Instructions

Parse raw HTML from a confluence.org point page. Useful when you've fetched the HTML yourself (e.g. via browser). Returns the same structured data as confluence_get_point.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude of the point (needed since it's not reliably in the HTML)
lonYesLongitude of the point
htmlYesRaw HTML content of the confluence.org page
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It communicates that the tool is a parser rather than a fetcher and that it returns the same data as confluence_get_point, but it does not mention behavior on invalid HTML, error handling, or coordinate validation. Reasonable but incomplete for a tool with no annotation safety profile.

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?

Two sentences with no filler. The core action is front-loaded, the usage condition follows immediately, and the output comparison to the sibling tool is packed into a short, skimmable clause.

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?

All three required parameters are fully documented, and the return type is anchored by referencing confluence_get_point's structured data. The description covers when to use it, what input to provide, and what to expect back. It is not exhaustive about errors or the exact output shape, but it is sufficient for an agent to invoke it correctly.

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 description coverage is 100%, with each parameter already meaningfully documented, especially the rationale for needing lat/lon. The description adds no additional parameter semantics beyond labeling html as raw HTML, so it meets the baseline but does not exceed it.

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 opens with a specific verb and resource: 'Parse raw HTML from a confluence.org point page.' The closing sentence ties it to the sibling tool's output, clearly distinguishing this parse operation from fetching via confluence_get_point.

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 a concrete use condition: 'Useful when you've fetched the HTML yourself (e.g. via browser).' It implies the alternative is confluence_get_point, but does not explicitly say 'use get_point when you have not fetched the HTML,' so exclusions are only 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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