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mason

mason

by adrianczuczka
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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get_impact

Trace historical co-change partners, related tests, and code references to assess pre-edit impact, with evidence from imports and paths; candidates are unproven dependencies.

Instructions

Trace historical co-change partners, related tests, and references with evidence: resolved imports, explicit paths, or uncertain name candidates. Candidates are not proven dependencies. Deterministic and read-only; no initialization or concept map required.

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": {
      "dir": "<dir>",
      "files": "<files>"
    },
    "name": "get_impact"
  }
}

Input Schema

NameRequiredDescriptionDefault
dirYesAbsolute path to the project root directory
filesYesFile paths or names to analyze (e.g., ['WeatherRepository.kt'] or ['src/services/auth.ts'])

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: deterministic, read-only, no prerequisite setup, and an important caveat that candidates are not proven dependencies (epistemic status of results). It still omits performance characteristics and the shape of returned results, so it falls short of fully rich behavioral disclosure.

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 dense sentences, correctly front-loaded with the purpose and then prerequisites and caveats. Every clause adds signal, though the colon-list of evidence types reads slightly stacked and could be tightened.

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 two-parameter, required-only tool with no output schema and no annotations, the description supplies purpose, prerequisites, determinism, and a caveat about result reliability. It is close to complete, missing only any hint at result volume or how to interpret the evidence categories it mentions.

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 coverage is 100%, so both parameters (dir, files) are already documented with examples in the schema. The description adds no syntax or format detail beyond what the schema provides, so the baseline of 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?

States a specific verb ('trace') and concrete resources (historical co-change partners, related tests, references), and even names the evidence types returned. It is clearly distinguishable from snapshot/decision siblings, though it never explicitly contrasts itself with the closest neighbors like get_context or full_analysis.

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?

It tells the agent a precondition ('no initialization or concept map required') and implies read-only analysis, but gives no explicit when-to-use-this-vs-alternatives guidance against get_context or full_analysis. Usage is inferable rather than stated.

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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