get-actor-runRead the status, storage identifiers, summary, and next step for an Actor run. A positive waitSecs value waits for a terminal state within the documented cap.
| Name | Required | Description | Default |
|---|---|---|---|
| runId | Yes | Actor run ID. | |
| waitSecs | No | Seconds to wait for a terminal state. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds meaningful wait semantics beyond the annotations: a positive waitSecs value waits for a terminal state, and a maximum cap is referenced. The read-only, idempotent, non-destructive profile is already covered by annotations, and the description is consistent with those hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. The core purpose and return fields are front-loaded, and the second sentence efficiently captures the important blocking behavior of waitSecs. Every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity read tool with only two parameters and strong annotations, the description is largely complete. Since there is no output schema, enumerating the returned categories (status, storage identifiers, summary, next step) helps the agent know what to expect, though exact response structure is not detailed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents runId and waitSecs. The description mostly paraphrases the schema's waitSecs behavior ('waits for a terminal state') and adds only the cap reference, so it provides no substantial additional parameter meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb ('Read') and clearly identifies the resource ('Actor run') plus the exact set of returned information: status, storage identifiers, summary, and next step. It is immediately distinguishable from the sibling abort-actor-run, which is the opposite operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes it clear this is the read-only observation tool for Actor run status, which is the right choice for polling or inspecting a run's current state and outputs. It does not explicitly say 'use abort-actor-run to cancel' or list exclusions, but the context is clear enough for a simple read tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most domain tools are well-scoped with explicit cross-references (e.g., FL DBPR vs. STR registry, Texas vs. multistate childcare). However, the evidence-gateway overlaps with EPA, U.S. property, and other specialized tools by describing similar intake categories, creating ambiguity about when to use the router versus the domain-specific tool.
The specialized tools consistently use the civicdataforge-- prefix with descriptive noun phrases, while the generic actor tools use imperative verb_noun style. The naming is readable and predictable within each subgroup, but the mixed conventions and the awkward doubled prefix in civicdataforge--civicdataforge-evidence-gateway prevent full consistency.
Fourteen tools is reasonable for a broad government-evidence server covering many data domains plus an async run lifecycle. The count is not excessive, though the gateway and several overlapping domain-specific tools add some redundancy.
The tool set covers a wide range of evidence domains and provides complete async workflow coverage: launch queries, check run status, fetch dataset items, read KVS records, and abort runs. Minor gaps remain, such as no explicit way to enumerate supported jurisdictions or sources, and the gateway's broad categories are underspecified.