Pause and reason about a situation. No side effects, no data changes — just structured thinking. Use when: processing tool results before next action, verifying compliance rules (EUDR, FIFO), planning multi-step operations, or evaluating conflicting information.
| Name | Required | Description | Default |
|---|---|---|---|
| thought | Yes | Your reasoning, analysis, or plan. Write out your thinking step by step. |
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?
With no annotations provided, the description carries the full burden and clearly discloses that the tool has no side effects and no data changes. It also clarifies that it is a non-observable reasoning action. Only minor extras, such as whether it consumes context or waits for external state, are omitted.
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 tight sentences front-load the core purpose and then immediately provide actionable use cases. Every sentence earns its place, with no filler or redundant restatement of the tool name.
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 single-parameter tool with no output schema, the description fully covers what the tool does, when to use it, and its safety profile. Nothing essential is missing for an agent to invoke it 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%, and the 'thought' parameter is well-documented in the schema as reasoning, analysis, or plan with step-by-step writing guidance. The description adds the 'structured thinking' framing but does not substantially expand on the parameter meaning, so the baseline 3 applies.
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 uses a specific verb ('Pause and reason') and clearly defines the resource ('a situation') with the qualifier 'structured thinking.' It distinguishes itself from sibling data-query tools by explicitly stating it has no side effects and no data changes, making its unique role unmistakable.
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?
Provides an explicit 'Use when:' list covering four distinct scenarios: processing tool results, verifying compliance rules, planning multi-step operations, and evaluating conflicting information. This gives an agent clear conditions for selecting this tool rather than a data-fetching sibling.
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 signal tools (front_run_watch, prediction_signals, wave_signal) serve similar purposes and could be confused, though each has a distinct data source. Similarly, soul_insights and soul_stack_feed both present agent-generated content, creating some ambiguity.
All names use snake_case, but there's no consistent pattern: some are verb-first (get_prices, search_products), some are brand-prefixed nouns (soul_bounties, wave_portfolio), and mixed usage like daloopa_query and soul_verify. The inconsistency is readable but not predictable.
16 tools for a multi-source market data server is reasonable; there are no outright redundant tools, though a few (think, fusion_capabilities) feel auxiliary. The count is slightly above ideal but well within acceptable bounds.
The server provides extensive read-only browsing (soul_bounties, soul_insights) but lacks corresponding action tools like claiming a bounty or purchasing insights, creating dead ends. For a 'market', there are no execute/trade/buy operations, leaving significant gaps for agent workflows.