morse_decodeDecode Morse code back to text. Accepts letters separated by spaces and words by "/" or " " (double space). Keyless, offline.
| Name | Required | Description | Default |
|---|---|---|---|
| morse | Yes | Morse code, e.g. ".... .. / - .... . .-. ." |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "morse": ".... . .-.. .-.. --- / .-- --- .-. .-.. -.."
+ },
+ {
+ "morse": "... --- ..."
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and no destructive behavior. The description adds valuable context: 'Keyless, offline' meaning no authentication and local execution, which goes 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 concise: two sentences that immediately state the purpose and key usage details, with 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 one-parameter tool with rich annotations and no output schema, the description sufficiently covers purpose, input format, and key behavioral traits (offline, keyless). The return value is obvious from the tool name.
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 examples. The description adds format rules not fully covered in the schema description (e.g., word separators), providing extra clarity 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 clearly states 'Decode Morse code back to text', using a specific verb and resource. It distinguishes from the sibling tool 'morse_encode' which 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 specifies input format details (letters separated by spaces, words by '/' or double space) and notes 'Keyless, offline'. However, it does not explicitly state when to use this tool versus alternatives like 'morse_encode'.
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.
Multiple tools blur together: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-variants, and the six polymarket_* tools plus bet_research heavily overlap in purpose. Descriptions are detailed and cross-reference each other, but an agent must read very long definitions to avoid misselection.
The set is consistently snake_case with helpful domain prefixes like ask_pipeworx, polymarket_*, and scan_*. Deviations such as deep_research, entity_profile, recent_alerts, and the bare verbs remember/recall/forget break a strict verb_noun pattern but remain predictable.
34 tools is heavy for one server, and several groups could plausibly be consolidated. However, the platform spans data lookup, research, prediction markets, memory, subscriptions, and utilities, so the breadth partially justifies the count.
The surface covers lookup, grounded verification, deep research, entity comparison, claim validation, prediction-market analysis, memory CRUD, subscription lifecycle, and discovery. There are no obvious dead ends, and gaps are minor or workaroundable.