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AleBrito124356

mcp-git-historian

Change coupling

change_coupling
Read-onlyIdempotent

Identify files that change together in commits to uncover hidden dependencies static analysis misses. Uses temporal coupling metrics like shared commits and degree.

Instructions

Temporal coupling: files that keep changing in the same commits, a hidden dependency static analysis cannot see (e.g. code and the test or config that must always be edited with it). Per pair: shared commits, each file's revisions, degree = shared / min(revisions) (1.0 = every change to the rarer file also touched the other) and jaccard = shared / union. Rename-aware; merges and huge commits are ignored.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNoMaximum number of pairs/partners to return.
fileNoOptional file (relative to the repository root): return only the files coupled to it.
sinceNoOnly count commits newer than this git date expression, e.g. '1 year ago', '6 months ago', '2025-01-01'. Empty string = all history.1 year ago
repo_pathYesAbsolute path to a local git repository, or to any folder inside one (a sub-folder scopes the analysis to it).
min_sharedNoMinimum number of shared commits for a pair.
max_files_per_commitNoSkip commits touching more files than this (mass reformatting, vendoring).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), yet the description adds real substance beyond them: rename-aware matching, and explicit exclusion of merges and huge commits. It also defines exactly how degree and jaccard are computed and what a 1.0 means, so the agent understands the semantics of the output.

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?

Three dense sentences, front-loaded with the core concept then the per-pair output fields and caveats. No filler; every clause (formulas, exclusions, rename-awareness) carries information the agent needs to interpret results.

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

Completeness5/5

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

With an output schema present the description need not enumerate return fields, and it still goes further by defining the metrics' meaning. Combined with the filtering caveats, an agent has everything required to call this correctly and interpret results.

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 every parameter (top, file, since, repo_path, min_shared, max_files_per_commit) is already documented, including defaults and date syntax. The description adds metric semantics (degree, jaccard, shared commits) but nothing extra about the parameters themselves, so the baseline 3 applies.

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?

States a specific analysis verb/resource: identifying files that change together in the same commits, and explicitly frames it as 'a hidden dependency static analysis cannot see', which distinguishes it conceptually from static-analysis-oriented siblings like hotspots or repo_summary. The reader immediately knows what the tool computes.

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?

Usage is implied rather than stated: the parenthetical example ('code and the test or config that must always be edited with it') suggests the investigative intent, but there is no explicit when-to-use, when-not-to-use, or named alternative among the ten siblings. Adequate but leaves the agent to infer routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.