Draconic Market Intelligence

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

The description adds significant behavioral context beyond annotations: it never buys/sells or accesses the broker account, does not create alerts, saves the conversation on successful calls, consumes one Draconic credit, and reports unsupported instruments before charging. This clarifies the side effects consistent with readOnlyHint=false and openWorldHint=true, with no contradiction.

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 purpose and covers necessary constraints, but it is wordy and contains repetition: 'Never buy, sell, enter, exit, or execute' largely duplicates the earlier 'Do not call this tool for requests to place, modify or cancel orders, execute trades.' A tighter edit would preserve clarity while reducing 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 complex tool with 10 parameters, an output schema, and annotations, the description is complete: it states scope, exclusions, market-wide behavior, credit consumption, conversation continuation, unsupported-instrument handling, and result formatting. Nothing an agent needs to select and invoke the tool correctly 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 coverage is 100%, so the baseline is 3. The description adds value beyond the schema by clarifying market_wide=true usage for NSE/US sector summaries without instruments, emphasizing that chat_id continues a prior Draconic chat, and instructing users to include position/thesis context in the question. This pushes it above baseline, though some parameter aliases 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 opens with a specific verb and resource: 'Ask analytical questions about supported instruments.' It enumerates concrete request types (options positioning, news context, comparison, timeframe conflict, thesis) and explicitly separates itself from execution, streaming, and unrelated tasks. This clearly distinguishes it from siblings like get_coverage and get_account_usage.

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 explicit when-to-use and when-not-to-use guidance: do not call for orders, executions, raw data streaming, or unrelated tasks; explain that limitation directly; check get_coverage for supported instruments/timeframes; set market_wide=true for NSE/US sector summaries. It is unambiguous about routing to alternatives.

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 state readOnly, idempotent, and non-destructive, and the description builds on this by adding 'without consuming a credit,' which is a meaningful behavioral guarantee. It also warns against inventing billing dates and against adding the free allowance to credits_remaining, which are important edge-case behaviors. No contradiction 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?

Two focused sentences with no filler. The core action and no-credit side effect are front-loaded, and the second sentence adds only essential caveats about null dates and free allowance handling.

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 operation with an existing output schema, the description covers the core semantics, side-effect behavior, and important edge cases. Explicit sibling routing is not strictly necessary because the tool's purpose and scope are fully clear.

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 100% schema description coverage, so there is nothing for the description to add about parameters. The baseline of 4 applies for zero-parameter tools; the description appropriately focuses on output semantics instead.

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 starts with a specific verb and resource: 'Read the authenticated user's Draconic plan and shared credit balance.' It is unambiguous about what the tool returns. It does not explicitly distinguish itself from sibling tools ask_draconic or get_coverage, but the resource scope is unmistakable.

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 when to use the tool: when you need the authenticated user's plan or shared credit balance. It also gives practical guidance about null billing fields for free/test accounts. It does not name alternatives or exclusion conditions, but the narrow scope makes misuse unlikely.

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 non-destructive behavior. The description adds meaningful behavioral context beyond those hints: no consumption of credit, no price data returned, and the exact meaning of availability.

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?

Three focused sentences with no wasted wording. The core action and scope are front-loaded, followed by necessary caveats about availability, credit, and prices.

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 a full output schema, fully documented parameters, and rich annotations, the description is complete. It explains the key non-obvious semantics (stored vs. live data, no credit cost) an agent needs to invoke and interpret 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?

Schema description coverage is 100%, so the baseline is 3. The description adds value by noting the default timeframe (5m), which is absent from the schema, and by reinforcing that each timeframe must be checked separately.

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 uses a specific verb ('Check') with a precise resource ('exact supported instruments for one requested timeframe') and clarifies scope ('Availability means stored data exists, not a guaranteed live feed'). It is clearly distinct from its siblings, which concern account usage and questioning Draconic.

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 clear operating context: check one timeframe at a time, handle additional timeframes separately, and interpret 'availability' as stored data rather than live feed. It does not explicitly name alternatives or say when not to use this tool, so it stops short of a 5.

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