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Browser flow runs

get_flow_runs
Read-only

A browser flow monitor's recent runs over a window (1h/24h/7d/30d): every declared step with its outcome and duration, the step a failure stopped on, and the page the browser saw. Use this to answer why a login check failed. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe monitor id (from `list_monitors`), of a `flow` monitor.
windowYesTime window: `1h`, `24h`, `7d`, or `30d`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
runsYes

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description reinforces it with 'Read-only.' The description adds behavioral context by specifying the time window options (1h/24h/7d/30d) and the type of data returned (every declared step, failure step, page). This adds value beyond the schema and annotation without contradicting them. No hidden side effects are mentioned, but the bar is met given the annotation.

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 two sentences, with the first packing all essential facts about the resource, data, and scope, and the second giving a practical use case. There is no redundant or filler language; every phrase contributes.

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?

With an output schema present, the description need not detail return formats. It explains what the tool returns conceptually, the windows, the monitor type, and a motivating use case. For a two-parameter read-only tool, this is complete.

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 already provides descriptions for both parameters with 100% coverage. The description only restates the window choices and confirms the id must be a flow monitor (already in the schema). No additional parameter semantics are added, so the baseline of 3 applies.

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 opens with a specific noun phrase ('A browser flow monitor's recent runs') and details the contents (steps, outcomes, durations, failure step, page). It clearly specifies the resource (flow monitor runs) and the action (get). It also distinguishes from siblings by focusing on recent runs with failure details, and even offers a concrete use case ('why a login check failed').

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear context for when to use the tool: 'Use this to answer why a login check failed.' It implies this is the diagnostic tool for inspecting individual runs and step outcomes. However, it does not name alternative tools or specify exclusions, so it falls short of full alternative 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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: flow runs, step trends, incidents, incident metrics, monitors, monitor history, org health, org usage, status pages, notification channels, regions, status pages lists, and tags. The get_ vs list_ distinction is consistent and each pair (e.g., get_monitor vs list_monitors) is clearly separated by depth of detail. No two tools appear to serve the same purpose.

Naming Consistency5/5

All tool names follow the verb_noun pattern with snake_case, using only 'get_' for single-item or aggregate detail and 'list_' for collections. Objects are consistently named (monitor, incident, status_page, org_*). This predictive pattern makes it easy to guess tool behavior from the name.

Tool Count5/5

At 15 tools, this server sits at the upper bound of the well-scoped range, yet every tool fills a clear niche: monitoring details, history, incidents, flow-specific analytics, org-level views, and reference data (regions, tags, channels). No tool feels redundant, and the count is appropriate for a read-only monitoring API.

Completeness4/5

The read-only surface is remarkably comprehensive, covering monitors, incidents, flow runs, step trends, status pages, notification channels, regions, tags, and org health/usage. The only notable gap is the lack of any mutation tools (e.g., update_monitor, acknowledge_incident) which the descriptions hint at but do not expose, so agents cannot act on the information—only observe.