Bitcoin cycle indicators: Pi Cycle, Mayer, 200W MA, Puell, S2F

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

Beyond the readOnly and openWorld annotations, the description discloses that it returns latest readings and Pi Cycle cross dates, optionally the daily series, and that data is 'recomputed nightly from a first-party close record since 2012.' It also clarifies 'Levels, not forecasts,' setting correct expectations about output nature. These are meaningful behavioral details not captured by 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 front-loaded with the usage condition and is reasonably efficient. The long enumeration of indicators is slightly repetitive with the title but serves to specify coverage. Every sentence contributes, though the list could be trimmed without losing much.

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 read-only tool with 100% schema coverage and no output schema, the description provides all an agent needs: the trigger scenario, the specific indicators covered, the return content (readings, cross dates, optional series), data source and update cadence, and a caveat ('Levels, not forecasts'). Nothing essential is missing.

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%, so the schema already documents both parameters fully. The description mentions 'optionally the daily series' and the nightly recomputation, which lightly reinforces include_points and data recency, but adds no syntax or format details 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 states a specific verb ('Call this when...') and a precise resource: Bitcoin cycle indicators, enumerating the exact indicators covered (Pi Cycle Top, Mayer Multiple, 200-week MA, 2-year MA multiplier, golden ratio multiple, profitable days, stock-to-flow, Puell Multiple, Bitfinex margin positioning). This clearly distinguishes the tool from siblings like get_market_indices or get_series, which are broader.

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 gives an explicit trigger: 'Call this when the user asks whether Bitcoin is near a cycle top or bottom by the classic indicators.' It does not name an alternative tool or state when not to use it, but the context is sufficiently clear that an agent can infer appropriate use.

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