List every Class H issue in the truth market, returning each issue's id, claim text, context, state, and divisiveness index in one call. Use this when the user asks what is currently being contested, which claims are open for validation, or which issues are most divisive right now.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive (destructiveHint: false), so the safety profile is clear. The description adds value by stating the scope ('every Class H issue') and the 'in one call' behavior, which implies a single response without pagination—useful context 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?
Two concise sentences front-load the verb and resource, then add usage guidance. Every word earns its place; there is no redundancy.
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 zero-parameter list tool with a rich output schema, the description fully covers what the tool does, when to use it, and what it returns. Sibling tool names provide alternative context. No major gaps.
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?
With zero parameters, the description has no parameter details to add. Per the rubric, 0 params sets a baseline of 4, and the description appropriately doesn't clutter with irrelevant parameter information.
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 a specific verb ('List') and resource ('every Class H issue in the truth market'), and enumerates the returned fields (id, claim text, context, state, divisiveness index). This clearly distinguishes it from sibling tools like get_issue or list_open_tasks.
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?
It explicitly tells when to use the tool ('when the user asks what is currently being contested, which claims are open for validation, or which issues are most divisive right now'). However, it does not mention when not to use it or suggest alternatives, so it misses the full when-not/alternatives criterion for a 5.
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 distinct resource or action: fetching challenge, corpus, issue, ledger, market, params, key, settlement, solution; listing issues, tasks, solutions; preparing and submitting work; and describing the protocol. There is no overlap or ambiguity among them.
All tool names follow a consistent verb_noun pattern with lowercase and underscores: get_*, list_*, prepare_*, submit_*, and describe_*. The pattern is uniform and predictable across the entire set.
With 15 tools, the surface is well-scoped for a domain that requires both read and write capabilities. Each tool contributes meaningfully without redundancy, and the count falls within the ideal 3-15 range.
The tool set provides full lifecycle coverage: understanding the write protocol, reading all relevant data (issues, markets, ledger, settlements, solutions, params), preparing work entries, and submitting them. There are no obvious gaps or dead ends for an agent to accomplish its goals.