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detect_citation_system

Detect citation system in Word: native, Zotero, Mendeley, EndNote, or plain text. Returns counts per system and flags split-brain mixes. Run before editing citations.

Instructions

Which citation system(s) the document uses: Word native (CITATION fields + sources store), Zotero (ADDIN ZOTERO_ITEM), Mendeley (ADDIN CSL_CITATION), EndNote (ADDIN EN.CITE), or plain typed text only. Counts per system across body, footnotes, and endnotes, plus a split_brain flag when more than one managed system is present (a split-brain bibliography: each manager only maintains its own fields). Run this BEFORE any citation work on an unfamiliar document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses that the tool counts citations per system across body, footnotes, and endnotes, and explains the split_brain flag and its meaning. This gives an agent a solid understanding of the tool's output behavior and scope.

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 compact yet information-dense: it lists the detected systems, the counting scope, the split_brain condition, and the recommended invocation timing. Every sentence contributes meaningful information without padding.

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?

For a preflight detection tool with an output schema, this description is complete: it explains what is detected, how results are structured (counts per location and flag), and when to invoke it. No critical information is missing for an agent to decide to use the tool.

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

Parameters2/5

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

The input schema has one required parameter, file_path, with 0% schema description coverage, but the tool description never mentions the parameter or how it should be provided. The parameter name is likely intuitive, but the description provides no added semantic value for 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 names a specific detection function, lists exactly which citation systems are recognized (Word native, Zotero, Mendeley, EndNote, plain text), and gives the technical markers used to identify each. This clearly distinguishes it from sibling tools like check_citation_parity or insert_citation.

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 explicitly states when to run the tool: 'Run this BEFORE any citation work on an unfamiliar document.' This is a clear usage context, but it does not name alternative tools or state explicit exclusion conditions, so it falls just short of full guidance.

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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