Galaxy Mind

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint. The description adds useful context beyond annotations by explaining the calculation (mined minus lost/seized/ETF/treasury coins) and the cohort breakdown, which reveals the dynamic nature of the output.

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 one sentence plus an explanatory clause. It is efficient and front-loaded with the main purpose. Slightly wordy with the formula but still concise.

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?

Despite no output schema, the description thoroughly explains what the float is, how it is computed, and which components are subtracted. This provides complete context for an informational tool.

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?

No parameters exist; schema coverage is 100% vacuously. The description adds no parameter semantics but it is not needed. Baseline score of 3 is appropriate.

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 clearly states the tool returns 'the Bitcoin float: how much BTC is realistically left to buy' and provides a detailed formula. It is a specific verb+resource that distinguishes from sibling tools like get_buying_gauge or get_treasuries.

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?

No guidance on when to use this tool vs alternatives. The description does not specify use cases or exclusions relative to siblings like get_buying_gauge or get_gauge_history.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, and openWorld hints. The description adds value by detailing the score range, the specific market signals included, continuous updates, and a methodology link. 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?

The description is a single, information-dense sentence with no wasted words. It conveys all necessary details efficiently, including a methodology URL.

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?

Given no output schema, the description adequately describes the return value (score, components, best window). It covers the essential information for a parameterless retrieval tool.

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 baseline is 4. The description effectively explains what the tool returns without needing to describe parameters.

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 the tool returns a Bitcoin Buying Gauge verdict as a 0-100 score, explains what higher values indicate, and lists the 10 weighted signals. It clearly distinguishes from siblings by focusing solely on the buying gauge, not other Bitcoin metrics like float or treasury.

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 usage for assessing entry timing based on the gauge, but it does not explicitly state when to use this tool versus alternatives like get_gauge_history or get_bitcoin_float. No when-not-to-use guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. Description adds valuable behavioral detail: returns entries in oldest-first order, and each entry includes date, score, and tier. No contradictions; description enriches 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 sentences concisely cover purpose, output format, and ordering. Front-loaded with key action. Every sentence adds value with 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 historical data tool with one parameter and no output schema, the description sufficiently explains inputs, outputs, and order. Could mention if pagination exists or max results, but likely not needed. Good balance for this complexity.

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 has 100% coverage for the single parameter 'days', but description adds critical info: default is 90, and values snap to nearest supported window (30, 90, 180, 365). This provides practical usage semantics not explicit in the schema.

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?

Description clearly states the tool returns 'Daily Buying Gauge score history' in order (oldest first) and specifies output fields (date, 0-100 score, tier). This distinct purpose is easily differentiated from siblings like 'get_buying_gauge' (current gauge) and 'get_treasury_history' (different metric).

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?

No explicit guidance on when to use this tool vs alternatives. The description implies it is for historical data, but does not state when not to use it (e.g., for current score) or compare with sibling tools. Context is clear but lacks exclusions or scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds behavioral context by specifying it's 'live' and detailing exact outputs (blocks, days, subsidy change), which is helpful for an agent beyond the 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?

A single sentence of 16 words that efficiently conveys the tool's purpose and outputs. No filler, front-loaded, and every word earns its place.

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?

Given zero parameters and no output schema, the description provides complete context: it's a live countdown with specific output fields. No gaps remain for an agent to invoke the tool 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 tool has zero parameters, so the description cannot add parameter semantics. Baseline score is 4 for no parameters, and the description correctly omits any param info.

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 clearly states the tool provides a live countdown to the next Bitcoin halving, listing specific outputs (blocks remaining, estimated days, month, block-subsidy change). This distinct purpose sets it apart from sibling tools like get_bitcoin_float or get_treasuries.

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 clearly implies the tool is used to fetch halving countdown data, with no parameters needed. While it doesn't explicitly state when not to use it or provide alternatives, the context is clear and no exclusions are necessary.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark it as read-only, open-world, and idempotent. The description adds behavioral context: it is a 'live' scoreboard (data may change), explains the three valuation lenses, and notes that CEBE/EV values are pending for some entries. This goes beyond annotations by disclosing data completeness and the meaning of returned fields.

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 front-loaded with the core purpose ('Live mNAV scoreboard for major public Bitcoin treasury companies') and then efficiently lists companies, explains key metrics, and notes pending data. Every sentence adds value without redundancy, making it concise yet thorough.

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?

Without an output schema, the description fully explains the returned metrics and their meanings, including the three valuation lenses and additional BPS metrics. It also warns about pending fields. However, it could be slightly more explicit about the output structure (e.g., array of objects), but the description is sufficiently complete for a read-only tool with no parameters.

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 input schema has zero parameters and schema description coverage is 100% (trivially), so the baseline is 4. No additional parameter info is needed, and the description appropriately focuses on what data is returned rather than input.

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 clearly states it provides a 'Live mNAV scoreboard' for major Bitcoin treasury companies, listing specific companies and detailing multiple valuation lenses (grossMNav, evMNav, netMNav) and additional metrics (bps, cebeBps, amplification). This distinguishes it from siblings like get_bitcoin_float and get_treasury_history by focusing on a specific financial analysis for treasury companies.

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 usage for obtaining current mNAV data but provides no explicit guidance on when to use this tool versus alternatives (e.g., for historical data, use get_treasury_history). While the tool's purpose is clear, the lack of when-not-to-use or alternative references limits its helpfulness for agent selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, and openWorld hints. The description adds value by specifying ordering (oldest first) and granularity (daily mNAV history), which are not in annotations. It does not contradict 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?

The description is a single, front-loaded sentence with no wasted words. Every part ('Daily mNAV history', 'one treasury ticker', 'oldest first') is meaningful.

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?

Without an output schema, the description should clarify the return structure. It mentions 'Daily mNAV history' and ordering, but does not specify fields (e.g., date, mNAV value) or pagination. It is adequate but incomplete.

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%, so the schema fully documents both parameters. The description does not add extra meaning beyond restating the ticker concept ('one treasury ticker') and the output ordering. Baseline score of 3 is appropriate.

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 clearly states the action (get history), resource (mNAV for a treasury ticker), and ordering (oldest first). It is specific and distinguishable from siblings like get_treasuries which likely returns current data.

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?

There is no guidance on when to use this tool over alternatives (e.g., get_treasuries for current values, get_gauge_history for other data). The description merely states what it does without usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate readOnlyHint and idempotentHint, which the description complements by explaining the verification date, stale flag based on 90-day window, and that the response reports stale match count. No contradictions.

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: first explains the core purpose, second adds key behavioral details and filter options. No unnecessary words, effectively front-loaded.

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?

The description covers the main functionality and the staleness attribute. While it lacks output schema or pagination details, the given information is sufficient for a search tool with annotations. Fairly complete given the tool's complexity.

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 75%, and the schema already describes the parameters. The description adds grouping by filter type but does not provide new meaning beyond the schema. Baseline 3 is appropriate.

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 clearly states it searches a human-verified directory of Bitcoin-accepting merchants, specifying the scope (on-chain + Lightning, real goods) and mentioning verification and staleness. This distinguishes it from sibling tools which are mostly data retrieval tools (e.g., get_bitcoin_float, get_halving_countdown).

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 explains the filters (free-text query, category, country) and the staleness feature, but does not provide explicit guidance on when to use this tool over alternatives or when not to use it. However, the sibling tools are clearly different, so usage context is generally clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.