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DigitalMicrograph MCP

DigitalMicrograph MCP

by wuchqwq
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

dm_stats

Compute min, max, mean, standard deviation, and quantiles for a full image or a bounded rectangular region to obtain ROI intensity statistics.

Instructions

区域统计：min/max/mean/stddev/分位数。可限定矩形区域。

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "dm_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault
rectNo像素矩形 [x0, y0, x1, y1]，右下边界不包含；必须完整位于图内，不舍入或裁夹；省略则整幅
image_idNo图像 id（来自 dm_datasets），或 "front" 表示前台窗口

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations supplied, the description carries the full burden; it does disclose the computed quantities (min/max/mean/stddev/quantiles), which is real behavioral information beyond the name. However, it says nothing about the return structure (single map? per-channel/per-frame?), data-source handling, or side effects, and "可限定矩形区域" merely restates the schema.

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?

Two short sentences, front-loaded with the metrics, no filler. Slight redundancy with the schema on the rect restriction, which does not earn its place.

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?

Two optional parameters and no output schema, so the description should at least sketch the return shape; listing metric names partially covers this but leaves the structure (keys, dtype, per-channel behavior) unspecified. Adequate minimum-viable, not complete.

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%, so both rect (half-open [x0,y0,x1,y1], must lie fully inside, no clamping) and image_id (id from dm_datasets or "front") are fully documented in the schema. The description adds nothing beyond that, so baseline 3 applies.

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?

"区域统计" states a concrete operation (statistics) plus the exact metrics computed (min/max/mean/stddev/分位数), so an agent knows precisely what it gets. It does not differentiate itself from siblings such as dm_2d_analyze or dm_profile, which could plausibly also summarize pixel data.

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

Usage Guidelines2/5

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

There is no statement of when to use this versus dm_2d_analyze, dm_profile or dm_2d_result, and no exclusions or prerequisites. The only usage hint is the optional rect, which is already implied by the schema.

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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