from_timestampConvert a Unix timestamp to an ISO-8601 UTC date + human forms. Auto-detects seconds vs milliseconds by magnitude (override with unit). Keyless, offline.
| Name | Required | Description | Default |
|---|---|---|---|
| unit | No | "s" or "ms" (default: auto-detect). | |
| timestamp | Yes | Unix timestamp. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "timestamp": 1704067200
+ },
+ {
+ "timestamp": 1704067200000,
+ "unit": "ms"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds valuable behavioral details: auto-detection of seconds vs milliseconds by magnitude, override with 'unit', and the keyless/offline nature, which enhances understanding 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?
Three concise sentences front-load the core action and constraints. No redundant information; every sentence serves a purpose. Highly efficient.
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?
The tool is simple with no output schema. The description covers input, auto-detection, and offline nature. However, the output format is only vaguely described as 'ISO-8601 UTC date + human forms' – could be more explicit about the exact return structure, but overall adequate for a straightforward conversion.
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 coverage is 100% with descriptions for both parameters. The description adds extra meaning by explaining the auto-detection logic and override capability, complementing the schema without repeating it.
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 'Convert a Unix timestamp to an ISO-8601 UTC date + human forms.' This specifies the verb (convert) and the resource (Unix timestamp to date/time), and distinguishes it from siblings like 'to_timestamp' (reverse) and 'relative_time' (relative time).
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 with 'Keyless, offline' suggesting it can be used without keys or network, but it does not explicitly state when to use over alternatives like 'to_timestamp' or 'relative_time'. Some context is provided but no direct when/when-not guidance.
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.
Many tools occupy heavily overlapping territory: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research, validate_claim, and even entity_profile/compare_entities all route questions to similar underlying data and could easily be misselected. The Polymarket suite adds another cluster of near-synonymous tools. Descriptions are detailed, but the boundaries require careful reading to keep straight.
Tool names mix imperative verbs (remember, subscribe, resolve_entity, validate_claim), noun-phrase descriptors (entity_profile, recent_changes, polymarket_edges), and time-utility names (now, from_timestamp, to_timestamp, relative_time). All-lowercase snake_case is consistent, but there is no unified verb_noun or domain-prefix pattern across the set.
35 tools is heavy and exceeds the comfortable 3-15 range, and most of them are unrelated to the server name 'Timestamp,' which adds confusion. The broad Pipeworx data scope justifies more than a tiny utility server, but the count still feels overstuffed and will burden tool selection.
For the broad data-research and prediction-market domain the set actually covers, the lifecycle is fairly complete: query, deep research, entity profiles, comparisons, claim validation, subscription management, and memory storage all have working operations. However, the surface is sprawling and includes one-off tools like generate_llms_txt and scan_dependency that do not fit any coherent domain, making completeness hard to assess and leaving a fuzzy, fragmented impression.