format_jsonPretty-print or minify a JSON string. indent sets spaces (default 2); pass 0 to minify to a single line. Keyless, offline.
| Name | Required | Description | Default |
|---|---|---|---|
| json | Yes | The JSON text. | |
| indent | No | Indent spaces (default 2; 0 = minify). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "json": "{\"name\":\"Alice\",\"email\":\"alice@example.com\"}"
+ },
+ {
+ "indent": 0,
+ "json": "{\"data\":{\"users\":[{\"id\":1}]}}"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations by stating it is 'Keyless, offline' and explaining the behavior of the indent parameter. No contradictions 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?
Two sentences with no wasted words. The main purpose is front-loaded, and the parameter behavior is efficiently described.
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?
All essential information is provided: purpose, parameter behavior, and safety traits via annotations. No output schema needed. Sufficient 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?
The schema already covers both parameters (100% coverage), but the description adds value by specifying default indent of 2 and that 0 means minify, clarifying the parameter's behavior.
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 states 'Pretty-print or minify a JSON string,' providing a specific verb and resource that distinguishes it from sibling tools like validate_json or query_json.
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 mentions 'Keyless, offline,' clarifying that no external dependencies are needed, but does not explicitly guide when to use this tool versus alternatives like query_json.
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 has a clearly distinct purpose, from querying data (ask_pipeworx) to entity profiling (entity_profile) to prediction market analysis (polymarket_arbitrage, polymarket_edges). Even similar tools like deep_research and ask_pipeworx are differentiated by scope (single vs. multi-facet). There is no ambiguity.
The vast majority of tools use snake_case (e.g., validate_claim, compare_entities). However, a few tools are single words (forget, recall, remember, subscribe, unsubscribe) which breaks the pattern slightly. This is a minor inconsistency.
With 33 tools, the set is on the larger side but well-justified by the broad scope of the server (data querying, entity research, prediction markets, JSON utilities, subscriptions, etc.). Each tool serves a specific need, making the count appropriate.
The tool surface covers virtually all expected operations for the domain: querying, profiling, comparison, change tracking, validation, discovery, subscriptions, memory, and utilities. No obvious gaps are present for the intended use case of accessing Pipeworx data and related tasks.