describe_cronParse and validate a cron expression (5 fields or an @alias) and describe it in plain English. Returns the parsed fields and whether it is valid.
| Name | Required | Description | Default |
|---|---|---|---|
| expression | Yes | A cron expression, e.g. "0 9 * * 1-5" or "@daily". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "expression": "0 9 * * 1-5"
+ },
+ {
+ "expression": "@daily"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint:false, covering the safety profile. The description adds valuable behavioral context by specifying the input format ('5 fields or an @alias') and the return behavior ('Returns the parsed fields and whether it is valid'). 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the primary action and includes all essential information without any fluff. 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 simple tool with one parameter and rich annotations, this description is complete: it states what the tool does, the input format, and the return values. No external context is missing for an agent to use the tool correctly.
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 parameter 'expression' is already well documented by the schema. The description adds the '5 fields or an @alias' detail, but this is essentially already conveyed by the schema's examples. Thus the description adds marginal value over the schema.
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 clearly states the tool's purpose with specific verbs ('Parse and validate') and a specific resource ('a cron expression'), and it describes the output ('describe it in plain English', 'Returns the parsed fields and whether it is valid'). This distinguishes it from all sibling tools, none of which perform cron expression parsing.
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 intended usage is implied by the description, but there is no explicit guidance on when to use this tool versus alternatives. No mention of exclusions or when not to use it, and no reference to sibling tools like 'next_runs' that might be related.
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.
Several tool clusters have blurred boundaries: ask_pipeworx_beta explicitly states it currently matches ask_pipeworx exactly, making them indistinguishable, and the five Polymarket tools (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, bet_research, polymarket_kalshi_spread) all target prediction-market opportunities with overlapping concerns. The meta-tools (discover_tools, suggest_questions, pipeworx_trending) and entity tools (entity_profile, compare_entities, recent_changes) are better separated by their descriptions, but the identical beta/stable pair alone forces a low score.
All tool names use snake_case, but the naming conventions are mixed: some follow verb_noun (describe_cron, next_runs, validate_claim), some are bare verbs (remember, recall, forget), and many are brand-prefixed noun phrases (ask_pipeworx, pipeworx_trending, polymarket_edges, bet_research). The pattern is readable and mostly predictable by prefix/domain, but there is no single consistent convention across the set.
33 tools is above the reasonable threshold for a focused server, and the count is especially disproportionate for a server named 'Crontab': only 2 tools (describe_cron, next_runs) actually deal with cron, while roughly 24 tools are Pipeworx data-query, prediction-market, and memory utilities unrelated to the server's apparent purpose. The bulk of the tool surface feels like it belongs on a different server, making the count mismatched with the stated scope.
For a cron-focused server, the surface is incomplete: it can describe cron expressions and compute next runs, but has no tool to create, update, or delete a scheduled cron job — subscribe/unsubscribe manage data-event subscriptions, not cron schedules. The Pipeworx data side is broad (lookup, grounded verification, entity profiles, comparisons, research), but that completeness belongs to a different domain and does not rescue the cron purpose implied by the server name.