Look up a Bitcoin/treasury metric definition from the Galaxy Mind glossary (mNAV, MVRV, Puell Multiple, in-play supply, accretion, …). Definitions are standalone and written to be quoted with attribution.
| Name | Required | Description | Default |
|---|---|---|---|
| term | Yes | Term name or slug, e.g. 'mNAV' or 'puell-multiple' |
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 and idempotentHint, so the description is not burdened with claiming idempotence. It adds valuable context that definitions are 'standalone and written to be quoted with attribution', which helps the agent understand output format and usage rights.
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?
Single sentence with 20 words, front-loaded with the core action, no fluff.
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 lookup tool with one parameter and no output schema, the description fully covers purpose, parameter examples, and output style. Combined with annotations, the agent has all necessary information.
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 coverage is 100% and includes an example ('mNAV' or 'puell-multiple'). The description adds additional examples ('MVRV, Puell Multiple, in-play supply, accretion'), providing richer context beyond the schema's single example.
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?
Clearly states the verb 'Look up' and the specific resource 'Bitcoin/treasury metric definition from the Galaxy Mind glossary'. Provides concrete examples (mNAV, MVRV, Puell Multiple) that distinguish it from sibling tools like get_bitcoin_float or get_buying_gauge.
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 implies use for retrieving glossary definitions, and sibling tool names provide enough context for an AI to distinguish. However, no explicit 'when to use' or 'when not to use' guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
