Adona Robot market data

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

With no annotations, the description carries the full burden and does so richly: exact auth header forms (Bearer adk_live_/adk_test_ or X-API-Key), the CONFLICTING_API_KEYS refusal when both are supplied, billing semantics (1000-bar slices rounded up, empty page free), the per-person minute ceiling tied to end_user_id, and that refusals map to /v1 codes.

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 core purpose is front-loaded and every clause carries information, but the auth and billing details make it a dense run-on that an agent must parse carefully. Nothing is wasted, yet the sentence structure could be tighter.

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 5-parameter read tool with no annotations and no output schema, the definition is nearly complete: it explains auth, pagination, limits, billing and error behavior. It stops short of describing the bar payload shape, though the pagination hint about next_before partially covers the return contract.

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 0%, so the description must compensate, and it does: it enumerates all timeframe values (D1..S1), bounds limit (1-5000), defines before as the prior response's next_before for reverse pagination, and explains end_user_id's role in rate limiting. Only symbol's syntax is left implicit, which is minor.

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?

States a specific verb and resource with scope and ordering: 'Candle history for one symbol, one page, oldest first.' The sibling tools (get_offer, list_symbols, quote_price_for) cover unrelated resources, so no sibling differentiation is needed, and the agent can tell exactly what this returns.

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?

Provides concrete usage mechanics: page backwards with 'before = the previous answer's next_before', and limit range 1-5000. It does not state when to prefer this over a sibling, but since the siblings are unrelated resources there is little ambiguity to resolve.

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?

No annotations are provided, so the description bears the full behavioral burden, yet it discloses nothing about mutability, auth requirements, rate limits, or freshness of the offer data. The content list hints at static reference data but no behavioral trait is actually stated.

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?

It is a single short fragment with no padding, so nothing is wasted, but the brevity comes from under-specification rather than discipline. The content list is front-loaded but carries little actionable information.

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?

An output schema exists, so return values need not be explained, but the description still fails to state the operation itself or any usage context. For a no-param retrieval tool an agent could call this, but nothing confirms intent against the three siblings.

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 per the rubric the baseline is 4. There is nothing for the description to clarify beyond the (empty) 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?

The description is a noun fragment ('The data offer: plans, prices, limits, trial, continuous feed, links') that enumerates content rather than stating an action. It never says what the tool does, and it does not distinguish itself from siblings like quote_price_for or list_symbols. The name get_offer carries the only real signal.

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 statement of when to use this tool, when not to, or which sibling to prefer. An agent has no routing guidance at all.

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?

With no annotations, the description carries the full burden. It discloses that this is a listing scoped to paid-plan symbols and what each entry contains, implying a safe read, but says nothing about pagination, rate limits, auth requirements, or what happens for unpaid accounts.

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 front-loaded sentence with no filler. It is a fragment rather than a full clause, but every word (scope, resource, returned fields) 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?

For a zero-parameter, read-only listing tool with an output schema already defining the return shape, the description supplies the essentials: what is listed, the plan constraint, and the fields. Only entitlement/auth behavior is left unaddressed.

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 the baseline is 4. There is nothing for the description to clarify beyond the implicit scoping to paid plans.

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 names the resource (symbols) and the scope (those a paid plan carries) plus the fields returned (name and class), which is enough to distinguish it from get_candles, get_offer, and quote_price_for. It lacks an explicit verb like 'list', but the intent is unambiguous.

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 when-to-use or when-not-to-use guidance and no named alternative. The only implicit hint is the 'paid plan' qualifier, which suggests an entitlement prerequisite but never states it as a condition for calling the tool.

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?

With no annotations, the description carries the full burden, and it does disclose useful behavior: it returns a plan plus a CHF total, and that amount is pre-VAT. It stops short of stating that this is a pure read-only calculation with no side effects, and says nothing about rate limits or permissions.

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 tight sentences, front-loaded with the verb and scope, with no filler. The parameter enumeration in the second half is dense but each clause earns its place by defining an input.

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?

An output schema exists, so return values need not be spelled out; the description still usefully previews that the answer is a plan plus a CHF pre-VAT total. For a three-parameter calculation tool this is close to complete, missing only routing guidance against get_offer.

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 0%, so the description must compensate — and it does, glossing all three params: simultaneous_connections ('at peak'), slices_per_month (defined as 'slices of 1000 bars'), and continuous_symbols ('symbols followed live continuously'). The unit clarification for 'slice' is genuinely valuable, though the required/optional distinction and the default of 0 for continuous_symbols are left to 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?

The description states a specific verb ('Price') and a concrete scope ('a month of usage') and enumerates the three cost drivers. It does not, however, differentiate itself from the sibling get_offer, which an agent could plausibly reach for on a similar pricing task.

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 statement of when to use this tool versus alternatives, no prerequisites, and no mention of the overlapping get_offer sibling. Usage must be inferred purely from the described inputs.

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