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voxmenthe

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by voxmenthe

analyze_recent_changes

Rank recent changes by impact with CodeRank to surface the most significant modifications, prioritizing review over a chosen period.

Instructions

Analyze recent changes using CodeRank to identify most important modifications. Aggregates changes over the last N days and ranks them by impact.

Args: repo_path: Repository path (absolute) days_back: Number of days to look back for commits target_branch: Branch to analyze (default: main) min_commits: Minimum commits to a file to be considered top_n: Number of top changes to return include_stats: Include detailed statistics

Returns: Ranked list of most important recent changes with metrics

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNo
days_backNo
repo_pathYes
min_commitsNo
include_statsNo
target_branchNomain
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It explains the core behavior (aggregates changes, ranks by impact) and mentions the return type, but does not disclose potential side effects, performance implications, or prerequisites (e.g., git history availability). The read-only nature is implied by 'analyze' but not explicitly stated.

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 well-structured and concise: a two-sentence summary, followed by a clear Args list and a Returns note. Every line provides necessary information without redundancy or fluff.

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?

Given the tool has six parameters and no output schema, the description provides adequate context by listing all parameters with explanations and summarizing the return value. It is not overly detailed about ranking metrics or edge cases, but covers the essential usage and output shape well enough for an agent to understand the tool's purpose and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has zero parameter descriptions, so the description's 'Args' block compensates by providing brief but meaningful explanations for each of the six parameters (e.g., 'days_back: Number of days to look back for commits'). While not extremely detailed, it adds value beyond parameter names and covers all parameters.

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 clearly states the tool's purpose: analyze recent changes using CodeRank to identify important modifications. It specifies the resource ('recent changes'), the method ('CodeRank'), and the scope (aggregated over the last N days, ranked by impact). This distinguishes it from siblings like 'coderank_analysis' which may be broader, and other change-related tools.

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?

The description implies when to use the tool ('to identify most important modifications' from recent commits) but does not explicitly provide usage vs. alternative tools or any exclusions. It gives context but lacks direct guidance on when not to use it or when to prefer a sibling.

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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