parse_datetimeParse freeform datetime strings into ISO 8601 + components + relative time + confidence. $0.001 USDC.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | Freeform datetime string in any format. | |
| timezone | No | IANA tz name (e.g. 'America/New_York'). | UTC |
| base_time | No | ISO 8601 reference; defaults to now UTC. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is known. The description adds value by disclosing the output envelope (ISO 8601, components, relative time, confidence) and the cost ($0.001 USDC), which are not captured elsewhere.
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, information-dense sentence followed by a price note. Every word contributes meaning, and the key action is front-loaded. No unnecessary repetition or filler.
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 parsing tool with 3 parameters, 100% schema coverage, and strong annotations, the description provides sufficient context. It even compensates for the absence of an output schema by listing the output components and includes the cost, making it complete for an agent to invoke 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%, with each parameter (input, timezone, base_time) already documented in the schema. The description does not add parameter-specific details beyond the general 'freeform datetime strings,' so it meets the baseline without exceeding 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 the tool's function with a specific verb ('Parse') and resource ('freeform datetime strings'), and lists concrete outputs (ISO 8601, components, relative time, confidence). This distinguishes it from all sibling tools, which are crypto/blockchain related.
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 provides clear context on when to use the tool (for parsing freeform datetime strings). It does not explicitly mention alternatives or exclusions, but given the sibling list contains no similar date-related tools, the intended usage is unambiguous.
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.
Each tool targets a clearly distinct function — anchoring, decoding, wallet intelligence, entertainment, etc. Even similar tools like decode_calldata vs decode_tx and intel_wallet vs screen_wallet are precisely separated by descriptions.
Most names follow a verb_noun pattern (anchor_hash, decode_calldata), but there are exceptions like aura_read (noun_verb), intel_wallet (noun_noun), and ledger_report (ambiguous). This mixed convention is readable but not fully consistent.
18 tools is slightly above the ideal range but not overwhelming. Each tool serves a specific purpose, and the count feels reasonable for the broad set of utilities offered.
The core utilities (anchoring, wallet intelligence, ledger accounting) are well-covered without obvious dead ends. Some domain-specific workflows could be expanded (e.g., verifying anchors), but the existing tools provide complete standalone operations.