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research.archaeology

Trace how a concept like error handling or auth flow evolved in a GitHub repo by analyzing git commit history and code changes. No external AI required.

Instructions

Trace how a concept evolved in a repo over time. Analyzes git commit history and code changes. No external AI required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesowner/repo
limitNoMax commits to analyze
aspectYesWhat to trace: 'error handling', 'auth flow', 'caching strategy'
pathHintNoNarrow to directory: 'src/auth/'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the data source (git commit history, code changes) and that no external AI is required, which is useful context, but says nothing about read-only safety, permissions, cost/latency, or output format for a multi-commit analysis.

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?

Three short, front-loaded sentences with no filler. The second sentence ("Analyzes git commit history and code changes") is mildly redundant with the first but still clarifies mechanism.

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?

Reasonable for a 4-param analysis tool with full schema coverage, but with no annotations and no output schema, the description should say more about what comes back (timeline, commit list, summary) or any bounds on the analysis.

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 repo, limit, aspect, and pathHint are already documented in the schema, and the description adds no format or usage detail beyond them. Baseline 3 holds when the schema does the heavy lifting.

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 and resource: "trace how a concept evolved in a repo over time", with git history and code changes as the mechanism. This is clearly distinct from generic siblings like code.trace or github.repo_overview, though no sibling is named explicitly to sharpen the boundary.

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?

No when-to-use guidance, no conditions, and no alternatives named. The agent must infer that this is for historical/evolution questions versus a static code lookup in code.trace or code.map. Nothing routes it against the ~30 siblings.

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