toolforte

Cron Parser

parse_cron

Read-onlyIdempotent

Parse a cron expression into a human-readable description and the next scheduled run times. Exact cron semantics: use this instead of interpreting cron syntax yourself.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`expression`	Yes	Cron expression, e.g. '0 9 * * MON-FRI'

Output Schema

TableJSON Schema

Name	Required	Description
`valid`	No	Whether the input passed every check
`result`	No	The result, when it is not an object
`nextRuns`	No
`description`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedSep 5, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "description": {
+      "type": "string"
+    },
+    "nextRuns": {
+      "items": {},
+      "type": "array"
+    },
+    "result": {
+      "description": "The result, when it is not an object"
+    },
+    "valid": {
+      "description": "Whether the input passed every check",
+      "type": "boolean"
+    }
+  },
+  "type": "object"
+}

First observedSep 1, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the output nature (human-readable text plus next scheduled run times) but leaves details like the number of returned run times and timezone handling unspecified. No contradiction with annotations.

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?

Two short sentences with zero filler. The action is front-loaded ('Parse a cron expression'), and the second sentence adds meaningful routing guidance without redundancy.

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?

For a simple, deterministic, read-only utility with one well-documented parameter, the description conveys the essential contract: parse a cron expression into a description and next run times. The only slight gap is the unspecified count or format of the returned run times, but the rich annotations and simple schema keep this adequate.

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?

Schema description coverage is 100%: the only parameter, 'expression', already has a description and an example ('0 9 * * MON-FRI'). The tool description adds no further parameter-level detail, 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 states a specific verb and resource ('Parse a cron expression') and the exact outputs ('a human-readable description and the next scheduled run times'). The phrase 'Exact cron semantics' further signals that this is the authoritative tool for cron interpretation, distinguishing it from the many unrelated sibling utilities.

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?

It explicitly advises 'use this instead of interpreting cron syntax yourself,' which tells the agent when to defer to this tool over self-implementation. It does not name alternatives or exclusions, but no sibling offers cron parsing, so this context is sufficient for selection.

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

A3.8/5.0

Disambiguation5/5

Every tool targets a distinct resource or action, and the detailed descriptions clearly separate near neighbors like generate_test_bsn versus generate_brp_test_data, read_page versus url_screenshot versus url_to_pdf, and image_compress/convert/resize. Even with 40 tools, there is no real boundary-blurring overlap.

Naming Consistency3/5

All names are snake_case and readable, but the set mixes conventions: verb_noun (generate_*, validate_*), noun_verb (pdf_merge, image_resize), conversion-style names (csv_to_json, html_to_pdf), and bare nouns (base64, qr_code_png). The groups are recognizable, but there is no single predictable pattern.

Tool Count2/5

Forty tools is an oversized surface for an agent to consider on every call, well above the point where tool selection cost starts to hurt. The broad purpose explains the count, but many one-off utilities could be grouped or exposed selectively.

Completeness3/5

The server covers many domains—encoding, Dutch test data, image/PDF handling, memory, and workflows—but several categories are partial: there are no reverse conversions like json_to_csv or html_to_markdown, no PDF text extraction, and no workflow create/update/delete tools. Agents can work around some gaps, but notable operations are missing.

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