format_numberFormat a number with grouping, fixed decimals, as a percentage, or in compact notation (keyless, offline). style = "decimal" (default), "percent", or "compact".
| Name | Required | Description | Default |
|---|---|---|---|
| style | No | decimal (default) | percent | compact. | |
| locale | No | BCP-47 locale (default "en-US"). | |
| number | Yes | The number to format. | |
| decimals | No | Fixed number of fraction digits. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "decimals": 2,
+ "locale": "en-US",
+ "number": 1234.567,
+ "style": "decimal"
+ },
+ {
+ "number": 0.456,
+ "style": "percent"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, establishing behavioral safety. The description adds value by noting the tool is 'keyless, offline', implying no external dependencies or authentication. However, it does not cover edge-case behaviors (e.g., error handling for invalid numbers). 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 sentence with two clauses, clearly stating the main purpose and available styles. It is front-loaded with the core action and includes additional context without extraneous words. Perfectly concise.
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 formatting tool with well-documented parameters and good annotations, the description covers the primary functionality and key constraints (keyless, offline). It lacks explicit mention of the return type, which is minor given the tool's simplicity. Could be slightly more complete but mostly adequate.
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 input schema already documents each parameter fully. The description merely restates the style options and adds the 'keyless, offline' context, which does not enhance parameter understanding beyond the schema. Baseline score of 3 is appropriate.
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 verb 'Format' and the resource 'a number' with explicit formatting styles (decimal, percent, compact). The note 'keyless, offline' further distinguishes it from similar tools like format_currency, making its purpose specific and unambiguous.
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 no guidance on when to use this tool versus alternatives such as format_currency. It lists available styles but does not explain the context or conditions for selecting one style over another, nor does it mention when not to use this tool.
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 tool clusters have overlapping functions: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly interchangeable, deep_research overlaps with the ask_pipeworx family, and the six Polymarket tools all analyze the same domain with subtle differences. discover_tools and suggest_questions also both serve as discovery entry points, making it difficult for an agent to confidently select the correct tool.
All names are snake_case, but there is no uniform structural pattern. Verb_object names like format_currency and resolve_entity coexist with noun_phrases like entity_profile and polymarket_arbitrage, bare verbs like remember and forget, and adjective_noun forms like recent_alerts. Cluster-specific prefixes are consistent, but the overall convention is mixed.
With 33 tools, the set is substantially over-scoped and exceeds the suggested 3-15 range. Many tools could be consolidated, such as the three ask_pipeworx variants, the six Polymarket tools, and the two formatting utilities. The broad domain justifies some size, but the count feels inflated and will burden agents with excessive choice.
The server covers many areas thoroughly: memory has remember/recall/forget, subscriptions have subscribe/unsubscribe/list/recent_alerts, and research tools span lookup, profiling, comparison, and verification. However, there are notable gaps: pipeworx:// citation URIs are returned but no tool explicitly fetches or reads a record by URI, and there is no direct way to manage account-level settings beyond memory. These missing operations force agents to work around limitations.