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change-impact-assistant

change-impact-assistant

by tanvi0102
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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analyze_current_change

Identify files likely affected by uncommitted git changes, with tiered confidence and plain-English reasons, to guide follow-up edits.

Instructions

Analyze the repo's current uncommitted git diff and report files that might also need attention, tiered by confidence (HIGH / MEDIUM / REVIEW SUGGESTED) with a plain-English reason for each. against compares to a specific ref instead of HEAD (e.g. "HEAD~1").

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": {
      "repo_path": "<repo_path>"
    },
    "name": "analyze_current_change"
  }
}

Input Schema

NameRequiredDescriptionDefault
sinceNo
againstNo
repo_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It explains that the tool analyzes the diff and produces a tiered report with reasons, and it clarifies how `against` changes the comparison base. The 'analyze and report' phrasing strongly implies a non-mutating read operation, though it doesn't state read-only explicitly.

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 two sentences with no filler. The core behavior and output structure are front-loaded, and the second sentence explains the one non-obvious parameter. Every sentence earns its place.

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 tool with no annotations and no output schema, the description does well: it specifies the input condition, output tiers, reason format, and the `against` behavior. The main gap is the unexplained `since` parameter, but an agent can still invoke the tool correctly for the primary use case.

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 0%, so the description must compensate. It does explain `against` with an example, but `since` is never described and `repo_path` is only inferable from its name. This is partial compensation for the missing schema documentation.

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 states a specific verb and resource: 'Analyze the repo's current uncommitted git diff' and report files 'that might also need attention.' It clearly differentiates the tool from siblings like get_changed_files by focusing on tiered follow-up attention rather than merely listing changes.

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: use this when you need analysis of the current uncommitted diff. It also explains the `against` option as a comparison to a specific ref instead of HEAD. It doesn't explicitly name alternatives or exclusions, but the intended use case is unambiguous.

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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