Isoba — Dollar & Crisis Index

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false, so the safety profile is covered. The description adds useful context by noting the inclusion of a data date and a weekly-change summary, but it does not disclose further behavioral traits like response format, caching, or update frequency.

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 and uses a single, dense sentence to enumerate the readings. While the nested parentheticals make it slightly heavy to parse, every clause adds substantive detail about the returned content without 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?

Given no output schema and no parameters, the description carries the burden of explaining what is returned. It names the four main reading categories and the weekly-change summary, which is sufficient for an agent to understand the tool's output surface, though it does not detail exact fields or formatting.

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, and the schema is empty by definition. Per the established baseline, a parameterless tool receives a 4 because there are no parameter semantics for the description to clarify.

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 returns today's Isoba readings with a data date, and enumerates the specific components (Dollar System Index, Crisis meter, market-top risk, recession risk, weekly changes). It distinguishes itself from siblings implicitly through 'today's' and 'this week,' but does not explicitly contrast with get_monthly_history or get_track_record.

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 explicit guidance on when to use this tool versus alternatives. The description only lists what the readings contain; it does not say to use it for current snapshots rather than historical tools, nor does it mention any prerequisites or exclusions.

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 read-only, idempotent, closed-world behavior, so the bar is lowered. The description adds genuinely useful substance beyond them: the data is double-averaged monthly (not raw), each month carries a zone, and availability windows differ (DSI since 2006, others since 1990), which tells the agent why early requests may return nothing.

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, front-loaded with the output definition followed by the use case, with no filler. The parenthetical availability note is dense but 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?

With no output schema, the description does the work of describing the return shape (monthly averages plus a zone per month), which is what an agent needs. Only minor gaps remain, such as whether the range is inclusive or how large a response can get.

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 every parameter, including the enum meanings and YYYY-MM defaults, is documented in the schema itself. The description only restates the two-month range without adding format or constraint detail, 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 states a concrete resource (monthly averages of one Isoba instrument) and the retrieval range (between two months), with useful coverage caveats per instrument. It implicitly separates itself from get_current_readings by returning historical averages rather than current values, but never names a sibling explicitly.

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?

"Use it for trends and to see what the instrument showed around past events" gives positive usage context but no exclusions or alternatives. An agent is left to infer that get_current_readings is for the present and get_track_record for something else.

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=false, so the safety profile is covered. The description adds real context the annotations cannot: the data is point-in-time, checked for look-ahead bias, and includes what the model does NOT catch. It says nothing about response size, latency, or format, but for a static read-only dataset that is minor.

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?

Front-loading is good — the point-in-time backtest frame leads — but the body is a single ~110-word run-on sentence with a long comma-separated inventory. The detail is useful, yet the structure costs readability and a bulleted breakdown would have served better.

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 and no parameters, the description must describe what comes back, and it does so thoroughly (16 crises, 3 recessions, 4 market tops, false-alarm rates, per-year summaries, known blind spots). Only the shape/format of the returned data is left unspecified.

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 takes zero parameters, so there are no argument semantics for the description to carry. Baseline 4 applies; the description spends its words on output content rather than inventing parameter guidance.

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 first clause states a specific verb and resource: how Isoba behaved when back-tested point-in-time over every working day since 1990, with an explicit enumeration of what the record contains (crises, recessions, tops, false alarms, per-year stats). It is clearly a historical-validation resource rather than a live-read tool. It never explicitly distinguishes itself from the sibling get_monthly_history, whose yearly/monthly history overlaps conceptually, so it stops short of a 5.

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?

"Call it before claiming reliability" gives a concrete condition for using this tool, implying when to consult it versus live readings. There are no explicit exclusions and no sibling named as the alternative, so the routing is clear but not fully specified.

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