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recent_activity

Retrieve recent project activity from your knowledge management system using natural language timeframes like 'yesterday' or 'last week'.

Instructions

Get recent activity for a project or across all projects.

Timeframe supports natural language formats like:
- "2 days ago"
- "last week"
- "yesterday"
- "today"
- "3 weeks ago"
Or standard formats like "7d"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNo
depthNo
timeframeNo7d
projectNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool retrieves ('Get') data, implying it's read-only, but doesn't mention behavioral traits like pagination, rate limits, authentication needs, error handling, or what 'recent activity' includes (e.g., events, changes). The timeframe format details are helpful but insufficient for a mutation-free tool with zero 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by specific timeframe examples. Every sentence earns its place by adding value—no redundancy or waste. The bullet-point list for timeframe formats is structured for clarity without verbosity.

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?

Given 4 parameters with 0% schema coverage and no annotations, the description is incomplete. It partially covers 'timeframe' but omits details for 'type,' 'depth,' and 'project.' An output schema exists, so return values needn't be explained, but for a read operation with multiple inputs, more parameter guidance 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?

Schema description coverage is 0%, so the description must compensate. It adds meaning for 'timeframe' by providing natural language and standard format examples, which clarifies semantics beyond the schema's title. However, it doesn't explain 'type,' 'depth,' or 'project' parameters, leaving three of four parameters with minimal guidance. The baseline is lowered due to incomplete compensation.

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: 'Get recent activity for a project or across all projects.' It uses a specific verb ('Get') and resource ('recent activity'), and distinguishes between project-specific and all-projects scope. However, it doesn't explicitly differentiate from sibling tools like 'search' or 'fetch' that might also retrieve activity data.

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 usage context by mentioning 'for a project or across all projects,' suggesting this tool is for retrieving activity logs. However, it provides no explicit guidance on when to use this versus alternatives like 'search' or 'fetch,' nor does it mention prerequisites or exclusions. The timeframe examples offer some operational context but not comparative guidance.

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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