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geo-osiris-mcp

geo-osiris-mcp

by osviel91
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

compare_dataset_to_layer

Compare a dataset against a geospatial layer to detect mismatches or candidates. Optionally stage imports for preview without writing, resolving, or publishing changes.

Instructions

Advisory dataset-vs-layer comparison.

With stage=false it performs zero writes and reports advisory-only signals. With stage=true (staging mode only) it creates exactly one staging import and previews bounded candidates; it never resolves, commits, publishes, or archives.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "layer_id": "<layer_id>",
      "filename": "<filename>"
    },
    "name": "compare_dataset_to_layer"
  }
}

Input Schema

NameRequiredDescriptionDefault
stageNo
mappingNo
filenameYes
layer_idYes
csv_contentNo
geojson_contentNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior5/5

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

With no annotations, the description fully carries the behavioral burden and does so well: it discloses zero writes in advisory mode, exactly one staging import in staging mode, bounded candidate previews, and explicit non-actions (never resolves, commits, publishes, or archives). This gives an agent a clear side-effect and 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?

The description is compact and well-structured: a one-sentence purpose followed by two mode-specific behavioral sentences. Every clause adds meaningful information, and the most important zero-write distinction is front-loaded.

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

Completeness3/5

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

The description is strong on side effects and mode boundaries, and an output schema exists so return values need not be explained. However, it does not clarify how the dataset is supplied, what mapping means, or what 'bounded candidates' concretely implies, so an agent still lacks key input-context needed to invoke the tool reliably.

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?

Schema description coverage is 0%, so the description must compensate for the six parameters, but it only explains the stage parameter's mode behavior. layer_id, filename, mapping, csv_content, and geojson_content receive no semantic explanation, leaving their roles and required format ambiguous.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear purpose: advisory dataset-vs-layer comparison, with mode-specific behavior. It does not explicitly name sibling tools, but the comparison focus and staging-only side effects distinguish it enough from list/get/inspect/summarize siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives useful mode-based usage guidance: stage=false for zero-write advisory checks, stage=true only in staging mode. However, it does not mention when to prefer this tool over alternatives like inspect_layer, summarize_import, or infer_csv_mapping, nor any explicit when-not-to-use conditions.

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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