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get_agent_runs

Retrieve recent agent run history with details on what ran, when, status, and token usage. Filter by date range or specific agent to review activity.

Instructions

Retrieve recent agent run history from the database.

Returns the log of past agent work — what ran, when, its status, and token
usage — for the dashboard or for reviewing recent activity. These rows are
written by log_agent_run. Results come back newest first.

Args:
    limit: Maximum number of runs to return, newest first (default 10).
    since: ISO date or datetime string; only runs at or after this time are
        returned. Empty string (default) returns runs from all dates.
    agent_slug: Filter to a single agent by slug, e.g. "librarian" or
        "metis". Empty string (default) returns all agents.

Returns:
    A text block listing the matching runs (run_id, agent, task summary,
    status, timestamp, token counts, model).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
sinceNo
agent_slugNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations exist, so the description carries full burden. It explains the tool reads from the database, returns newest-first results, and details the output content (run_id, agent, task summary, status, timestamp, token counts, model). No destructive behavior is implied, and the read-only nature is clear.

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 with a one-sentence purpose, a paragraph on what is returned, a bulleted Args section, and a Returns section. Information is front-loaded and every sentence adds value without redundancy.

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?

Given the simplicity of the tool (3 optional parameters, no nested objects, has output schema), the description covers purpose, parameters, return format, and even the related writing tool. It is fully sufficient for correct invocation without further context.

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

Parameters5/5

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

Schema description coverage is 0%, but the description's Args section thoroughly documents all three parameters: limit (default 10, newest first), since (ISO date/datetime, empty returns all), and agent_slug (filter by slug, empty returns all). This adds significant meaning beyond the type/default in the schema.

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 retrieves recent agent run history from the database, specifying the resource (agent runs) and action (retrieve). It distinguishes from sibling tool log_agent_run by noting that tool writes these rows.

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 mentions use cases ('for the dashboard or for reviewing recent activity') and references the writing tool, but does not provide explicit guidance on when to use this tool versus other retrieval tools like search_memory or search_session_memory. No exclusions or alternatives are given, so only adequate for a 3.

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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