get_field_guideStatic, versioned dictionary of every field this surface emits: unit, value set where the producer has one, and a one-sentence meaning, plus the shared response conventions (tier, delay, timestamps, and how missing data is reported). No inputs; call once per session.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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, idempotentHint, and non-destructive behavior. The description adds meaningful context beyond that: the data is static, versioned, and intended to be called once per session, plus it discloses what information the field guide contains. This goes beyond the annotation baseline.
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 compact and information-dense. The first sentence front-loads the core nature ('Static, versioned dictionary') and enumerates the contents efficiently. The second sentence handles usage and invocation. No unnecessary words or repetition.
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?
With no output schema present, the description does the necessary work of explaining what the tool returns: field names, units, value sets, meanings, and shared response conventions. It also gives session-level usage guidance. This is complete for a tool of this simplicity.
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?
There are zero parameters, so the schema is fully clear. The description reinforces this with 'No inputs,' which is sufficient. No additional parameter semantics are needed.
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 clear purpose: a static, versioned dictionary of every field the surface emits, with units, value sets, meaning, and shared response conventions. This clearly distinguishes it from siblings like get_day or get_regime, which fetch specific data, whereas this tool provides schema-level reference information.
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 explicitly says 'No inputs; call once per session,' which is a direct usage instruction for a reference tool. It doesn't explicitly name alternatives or exclusions, but the context of a field dictionary makes its role obvious relative to the data-fetching sibling tools.
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.
Most tools have clearly distinct purposes, but get_regime is a lightweight subset of get_market_structure, and get_day versus get_regime_segments both target historical replay data with different granularity. Descriptions are clear enough to prevent serious misselection, though some overlap exists.
Tool names consistently follow a verb_noun pattern: get_* for data retrieval, list_* for enumeration, subscribe_*/unsubscribe for lifecycle actions. The naming is predictable and scannable across the whole set.
Nine tools is well-scoped for this server's purpose: current market structure, regime snapshots, historical replays, a field guide, and subscription management. Each tool occupies a clear functional slot without unnecessary bloat.
The surface covers the core domain completely: current data, lightweight regime checks, historical date discovery and replay, field semantics, and full event-subscription lifecycle. No obvious dead ends or missing operations for the stated purpose.