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OverviewDiscussionsAdmin

actor_history

Read-only

How have one tracked actor's usage, run completion and primary event price changed by day? Uses compact official Apify Store history exports; dates are snapshot filenames, not verified per-actor observation times. days is a UTC calendar window ending today (1-365). Missing days stay absent; event rates are not total cost or necessarily per result.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "actor_id": "<actor_id>"
    },
    "name": "actor_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNo
actor_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the read-only, non-destructive, closed-world profile, and the description adds real behavioral caveats: dates are snapshot filenames rather than verified per-actor observation times, missing days stay absent, and event rates are not total cost nor necessarily per result. That goes meaningfully beyond the annotations, though nothing is said about response shape or error behavior.

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 tight sentences, front-loaded with the core question and followed by data-provenance and interpretation caveats. Dense but each sentence carries distinct information; no filler.

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?

With no output schema, the description does the work of setting expectations about the data source and rate semantics, which is the main interpretive risk. It stops short of describing what a returned series looks like or what happens when the actor is untracked.

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?

Schema coverage is 0%, so the description must carry the load. It defines days as a UTC calendar window ending today with a 1-365 bound (beyond the schema's bare min/max/default) and frames actor_id as a tracked actor, which hints at a prerequisite constraint not expressed in the schema.

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 resource (one tracked actor) and the three tracked series (usage, run completion, primary event price) over a daily window. This is clearly distinguishable from the sibling compare_*/find_* tools, though the question phrasing is slightly indirect rather than a direct verb statement.

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?

Usage is implied (trend/history lookup for a single tracked actor) but there is no explicit when-to-use, when-not-to-use, or pointer to a sibling when the actor is not tracked. The agent must infer that 'tracked' is a precondition.

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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