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jamesfishwick

Slipbox MCP Server

slipbox_refresh_clusters

Regenerate cluster analysis by detecting tag co-occurrence and link patterns, then save the report to a JSON file.

Instructions

Regenerate cluster analysis and save report.

Analyzes all notes for emergent clusters based on:

  • Tag co-occurrence (tags that frequently appear together)

  • Connection patterns (notes that link to each other)

  • Structure note coverage (which clusters already have structure notes)

Results saved to ~/.local/share/mcp/slipbox/cluster-analysis.json

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are present, so the description must carry the behavioral disclosure burden. It states that the tool regenerates analysis and saves to a file, implying a write operation. The specific output path is given, but it does not mention whether it overwrites the existing file, whether it is idempotent, or any potential side effects. There is no explicit statement about mutation or reversibility.

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 concise and well-structured: a one-sentence purpose followed by a bulleted list of analysis criteria. Every sentence earns its place, with no redundancy or fluff.

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 no-argument tool with no output schema, the description covers the purpose, input data, analysis dimensions, and output file. It does not explicitly describe the report format or return value, but saving to a file is sufficiently clear. The sibling tools (get_cluster_report, create_structure_from_cluster) provide additional context for how the output is used.

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?

The tool has zero parameters, so the baseline is 4. The description adds value by explaining the implicit inputs: all notes, tags, connections, and structure note coverage. This gives meaning beyond the empty schema.

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 'Regenerate cluster analysis and save report', which is a specific verb+resource. It further details the analysis criteria (tag co-occurrence, connection patterns, structure note coverage), and the output path. This distinguishes it from sibling tools like get_cluster_report, which likely reads the existing report.

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 gives clear context: it analyzes all notes and saves a report, implying it is used to refresh cluster data. However, it does not explicitly mention when to use it instead of alternatives like get_cluster_report or after specific changes. The when-not guidance is implicit rather than explicit.

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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