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Ground Truth - Fresh Evidence for AI Agents

by io.github.anish632

Create Monitor

create_monitor

Create a persistent monitor that tracks a URL, pricing page, package version, endpoint status, vendor claim, or custom keyword pattern over time. Monitors run automatically on their configured schedule (hourly/daily/weekly) via the Cloudflare cron trigger, or on demand with run_monitor_now. Results are stored durably by account. A free watch key includes three daily or weekly monitors; paid plans add hourly schedules and higher limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesHuman-readable name for this monitor.
scheduleNoHow often the monitor runs automatically. manual means only via run_monitor_now.daily
target_typeYesWhat to monitor. url/endpoint: HTTP reachability and status. pricing_page: pricing signals (prices, plans, free tier). package: package version on npm or pypi (target_value as 'npm:pkg-name' or 'pypi:pkg-name'). vendor_claim: keyword presence at a URL (target_value=claim text, instructions=URL to check). custom_prompt: comma-separated keywords checked against a URL (target_value=URL, instructions=keywords).
instructionsNoSupplementary instructions. For vendor_claim: the URL to check. For custom_prompt: comma-separated keywords. Optional for other types.
target_valueYesPrimary target. For url/endpoint/pricing_page/custom_prompt: a public https URL. For package: 'npm:package-name' or 'pypi:package-name'. For vendor_claim: the claim text to search for.
notification_destinationNoOptional HTTPS webhook URL. A POST is sent only when a scheduled check detects a change; no API key is included.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUnique monitor ID.
nameYesMonitor name.
errorNoError message if creation failed.
scheduleYesMonitor schedule.
created_atYesCreation timestamp ISO 8601.
target_typeYesMonitor target type.
target_valueYesMonitor target value.
active_monitor_limitNoMaximum active monitors included in the current plan.

TDQS

A4.5/5.0
Behavior5/5

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

With no positive annotations to lean on, the description carries the behavioral burden and does so well: it discloses persistence, automatic scheduling via Cloudflare cron, durable per-account storage, and plan-based limits. It also notes on-demand execution and mentions that free tiers restrict hourly schedules, which is important operational context.

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 three sentences long, front-loaded with the core purpose, and every sentence adds meaningful context: scheduling, on-demand execution, durability, and plan limits. There is no filler or redundant restating of the title.

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?

For a tool with six parameters, a complete input schema, and an output schema, the description covers the essential behavioral and operational context an agent needs. It explains what is created, how it runs, where results are stored, and what constraints apply, leaving no critical gap.

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 covers 100% of parameters with detailed descriptions and enums, so the description does not need to repeat parameter-level detail. The tool description adds no extra parameter guidance beyond the schema, which is acceptable given the schema's completeness.

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 identifies the action ('create a persistent monitor') and the resource it operates on, covering the main target types and distinguishing itself from on-demand execution via run_monitor_now. It is far more specific than the title alone and differentiates from siblings like delete_monitor or list_monitors.

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 explains how monitors run automatically or on demand, and it references run_monitor_now as the invocation path, which gives useful context. It does not explicitly contrast with one-off check tools like check_endpoint or verify_claim, but the persistent-monitor framing makes the primary usage scenario clear.

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

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there are several lightly overlapping pairs (check_endpoint/preflight_endpoint, check_pricing/compare_pricing_pages, estimate_market/compare_competitors, test_hypothesis/verify_claim). The detailed descriptions and explicit 'do not use for' notes mitigate confusion, so misselection is unlikely.

Naming Consistency5/5

All tool names follow a consistent lowercase snake_case verb_noun pattern (e.g., check_endpoint, create_monitor, verify_claim). Even compound verbs like preflight_endpoint and run_monitor_now adhere to the same structure, making the naming fully predictable.

Tool Count4/5

19 tools is slightly heavy but reasonable for the broad scope covering endpoint checks, pricing, compliance, package research, claim verification, and monitor lifecycle. Each tool has a distinct role, though the count edges close to the 'heavy' range.

Completeness4/5

Core workflows are well-covered: create/list/delete/get/run/preview monitors, single and comparative pricing checks, endpoint and security verification, and claim testing. Minor gaps exist, such as no update_monitor tool or a way to explicitly verify a claim without pre-supplied evidence URLs, but these are workable.

Resources