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get_contribution_activity

Analyze GitHub contribution activity to track commits, repositories, streaks, and development patterns for insights into coding habits and productivity trends.

Instructions

Analyzes contribution activity and returns metrics including: total commits, repositories contributed to, most active day, and contribution streak. Useful for understanding development patterns and activity trends.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
use_cacheNoWhether to use cached data (default: true)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions what metrics are returned, it doesn't describe important behavioral aspects such as data sources (e.g., GitHub API), time ranges covered, authentication requirements, rate limits, or error handling. The description adds some context about the analysis but leaves significant gaps for a tool with no annotation coverage.

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?

The description is appropriately sized with two sentences: the first states the purpose and lists metrics, and the second provides usage context. It's front-loaded with key information and avoids unnecessary repetition. However, the second sentence could be more specific to enhance clarity without adding bulk.

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

Completeness2/5

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

Given the tool's complexity (analyzing contribution activity with multiple metrics), lack of annotations, and no output schema, the description is incomplete. It doesn't specify data sources, time frames, or what the returned metrics look like (e.g., formats, units). For a tool with no structured output and behavioral gaps, more detail is needed to be fully helpful.

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?

The input schema has 1 parameter with 100% description coverage, providing clear documentation for 'use_cache.' The description doesn't add any parameter-specific information beyond what's in the schema. According to the rules, with high schema coverage (>80%), the baseline is 3 even with no param info in the description, which applies here.

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?

The description clearly states the tool's purpose with a specific verb ('analyzes') and resource ('contribution activity'), and lists concrete metrics returned (total commits, repositories contributed to, most active day, contribution streak). However, it doesn't explicitly differentiate from sibling tools like 'get_recent_commits' or 'get_repository_stats', which might also provide overlapping activity metrics.

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 provides implied usage context by stating it's 'useful for understanding development patterns and activity trends,' which suggests when this tool might be appropriate. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_recent_commits' or 'generate_portfolio_summary,' and doesn't mention any prerequisites or exclusions.

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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