parse_durationParse an ISO 8601 duration string (e.g. "PT1H30M", "P1Y2M10DT2H") into its components and an approximate total in seconds (keyless, offline). Note: months=30d, years=365d for the estimate.
| Name | Required | Description | Default |
|---|---|---|---|
| duration | Yes | An ISO 8601 duration, e.g. "P1DT2H30M". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "duration": "PT1H30M"
+ },
+ {
+ "duration": "P1Y2M10DT2H"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate read-only and idempotent behavior, which the description complements by noting 'keyless, offline' and detailing the approximation for months and years. This adds useful context beyond 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 two sentences, front-loaded with the core purpose, and every word adds value. No unnecessary information.
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 no output schema, the description adequately explains what the tool returns (components and total seconds). It is sufficient given the tool's complexity.
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?
With 100% schema description coverage, the schema already documents the parameter. The description provides examples but does not add significant additional meaning beyond 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 uses a specific verb 'Parse' and resource 'ISO 8601 duration string', clearly defining its function. It distinguishes itself from the sibling tool 'format_duration' which likely performs the reverse 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 implies usage for parsing durations but does not explicitly state when to use this tool versus alternatives. No exclusions or alternative suggestions are provided.
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.
The tool set includes several overlapping tools: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded serve very similar purposes with only subtle differences in behavior (beta/grounded). Additionally, deep_research and validate_claim partially overlap with these. The prediction market tools are numerous but distinct, and memory/duration tools are clear. Overall, an agent would face some confusion when selecting among the ask_pipeworx variants.
Most tools use consistent underscore_case with descriptive verb_noun patterns (e.g., list_subscriptions, resolve_entity, validate_claim). A few memory and subscription tools are single-word verbs (forget, recall, remember, subscribe, unsubscribe), which deviates slightly but remains readable. Overall naming is predictable and clear.
With 33 tools, the server is on the heavier side. The server covers a broad scope (data queries, prediction markets, AI visibility, memory, utilities, subscriptions), which justifies many tools, but some feel redundant (e.g., three variants of ask_pipeworx, multiple polymarket edge tools). A more focused set (around 20-25) would be more typical for coherence.
The tool surface is extensive, covering factual Q&A via a universal router, entity profiles, comparisons, prediction market analysis, memory, subscriptions, AI visibility, and utilities. The meta-tool ask_pipeworx provides access to thousands of structured sources, so most data needs are addressable. Minor gaps include no direct tool for specific SEC filing retrieval beyond the meta-router, but this is covered indirectly.