Stock Market Data MCP

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

No annotations exist, so the description carries full burden. It disclosed free/paid tiers, pricing, error recovery (402), payment retry logic, and auth bypass. Missing are rate limits and behavior on invalid tickers, but the core payment-related behaviors are well covered.

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 concise and well-structured: a one-sentence summary followed by detailed notes. No unnecessary words. Could benefit from slight structural formatting (e.g., line breaks) but is clear as is.

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 the tool's complexity (pricing, error handling), the description is comprehensive. It covers usage, payment workflow, and auth. With an output schema present, return values are covered elsewhere. Minor omission: no mention of error codes beyond 402 or output format, but still strong.

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 covers 100% of parameters with descriptions. The description adds critical context beyond schema: explains free vs paid tiers and how to use payment_tx parameter. It clarifies the retry process and auth bypass, giving agents actionable understanding.

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 begins with a clear verb and resource: 'Get latest quotes for many tickers'. It lists the specific data fields (price, change, volume, etc.) and distinguishes from sibling tools like 'quote' (single ticker) and others that serve different purposes.

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 when to use (batch quotes), tier limitations (free up to 10, paid above), pricing, and error handling (402 with payment_tx). It also mentions auth bypass. However, it does not explicitly state when not to use (e.g., for a single ticker use 'quote') or compare with 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?

With no annotations, the description fully discloses behavioral traits: brief expires at next midnight UTC, cost per call, payment flow on 402, provenance attestation, and bearer key bypass. No contradictions with missing 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 concise with no wasted words. The first sentence front-loads the core purpose, followed by necessary details about payment and expiration. Every sentence adds value.

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 all critical aspects: purpose, payment, expiration, error handling (402), and special bypass. With an output schema present, return values need not be described. The description is complete for an agent to correctly use the 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?

Schema covers 100% of parameters. The description adds context beyond the schema, especially the payment flow explanation for payment_tx and the default date behavior, enhancing the agent's understanding of parameter usage.

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 a curated daily market brief with specific contents (top gainers/losers, active names, sector performance, 52-week highs/lows). It distinguishes itself from siblings like quote or sector_performance by being a comprehensive daily summary with provenance attestation.

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 explicitly states the payment requirement ($20 USDC), default date behavior, expiration, and the exact procedure for handling a 402 response (pay and re-call with payment_tx). It also notes that a Bearer key bypasses payment, providing clear guidance for the agent.

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 present, so the description must carry the full burden. It does not disclose whether the tool is read-only, requires authentication, or has any side effects. It only states it provides 'details' without behavioral specifics.

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 two sentences but the first sentence is a label and the second is a rambling explanation. It could be more concise by focusing on what the tool returns rather than mixing in usage instructions for other features.

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 there is an output schema (not shown), the description should clarify what information is returned. It only says 'details' and mentions attestation and sibling servers, which is insufficient to understand the tool's output or structure.

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 input schema is fully covered (100%). The description adds context about the protocol and attestation, but since there are no parameters, the baseline of 4 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 mentions 'FoundryNet Data Network + MINT Protocol details' but does not specify a clear verb and resource. It is unclear what the tool actually does (e.g., retrieves, displays, or explains). The reference to attesting market analysis is tangential and does not define the tool's primary function.

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 or when to prefer alternatives. The phrase 'FREE' and mention of sibling servers imply a context, but no clear use-case or exclusion criteria are 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?

With no annotations, the description carries the full burden. It discloses that Greeks are not provided, that IV/OI/volume are included, and explains the payment behavior (free allowance, cost per query, 402 handling, auth bypass). This provides good transparency about the tool's behavior and requirements.

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 structured into three concise paragraphs, front-loading the core purpose. It includes necessary detail without extraneous content. Could be slightly more compact, but the payment explanation justifies the length.

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 aspects: what data is returned, what is not included, and payment handling. It does not detail free tier limits or data freshness, but the existence of an output schema reduces the need to describe return values. Overall, it is sufficiently complete for a data 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?

Schema description coverage is 100%, baseline is 3. The description adds value by explaining the payment_tx parameter in context of 402 handling ('pay the returned Solana memo and re-call'), which goes beyond the schema's brief description. This additional context merits a 4.

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 verb 'Get' and the resource 'option chain for a ticker', listing the specific data fields provided (calls/puts, strike, last price, bid/ask, etc.) and explicitly notes what is not included (Greeks). This distinguishes it from sibling tools like quote or batch_quote.

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 when to use the tool (to get option chain data) and provides detailed payment handling instructions (free allowance, 402 error, payment_tx parameter). However, it does not explicitly contrast with sibling tools or state when not to use it, so it loses a point for lacking comparative guidance.

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 fully carries the burden. It discloses the paid nature ($0.01 per query after free allowance), the 402 error recovery flow (returned memo, re-call with payment_tx), and an alternative authentication method (Bearer key bypass). This is thorough and helps the agent anticipate side effects.

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 concise with two sentences: first defines purpose, second explains payment behavior. Both sentences are necessary and front-loaded. Could be slightly more structured but overall efficient.

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 5 parameters (1 required) and an output schema, the description covers essential behavioral context (payment, defaults) and intended use (charting, backtesting). It does not detail return format, but the output schema exists to fill that gap. Slightly missing is explicit mention of data frequency or limitations.

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 baseline is 3. The description adds value by explaining the payment-related parameter payment_tx in context of the 402 flow, and implies the meaning of period and interval through examples (e.g., '6mo' default). However, it does not elaborate on every parameter beyond what the schema already documents.

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 'Get OHLCV price history for a ticker' with specific resource types (open/high/low/close/volume bars). It distinguishes from sibling tools like quote (current price) and options_chain by focusing on historical price data for charting, backtesting, and technical analysis.

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?

Description specifies usage context (charting, backtesting, technical analysis) and provides payment handling instructions (free allowance, 402 error resolution with payment_tx). However, it does not explicitly state when not to use this tool or compare with alternatives like quote or batch_quote.

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 provided, so description carries full burden. Discloses data source (snapshot refreshed every 30 minutes, live fallback on cold cache) which adds useful behavioral context. Does not mention rate limits, error handling, or auth requirements.

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 sentences, no filler. Front-loads purpose and returns, then adds behavioral details. Every sentence 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?

Tool is simple (1 param) and output schema exists, so description needn't explain return values fully. Lists all returned fields, mentions data freshness, and sibling tools are provided. Lacks error handling details but adequate for 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 100% so baseline is 3. Description reinforces the ticker parameter with example (AAPL) but adds no new semantic meaning beyond what the schema already provides.

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 'get the latest stock quote for a ticker' and lists specific fields (price, change, etc.). Distinguishes from siblings like batch_quote and price_history by implication, but not 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?

Describes itself as 'the gateway tool every agent tracking equities needs' implying it's the entry point, but provides no explicit when-to-use, when-not-to-use, or alternatives. Mentions data freshness constraint (30-min snapshot) but no guidance on selecting among siblings.

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 carries the full burden. It explains the read-only screening behavior, payment mechanics (free tier, per-query cost, 402 handling), and that it returns stocks ranked by market cap. However, it does not mention any rate limits or data freshness, leaving minor gaps.

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 concise with two paragraphs: the first covers the core screening purpose and alternative tool; the second covers the payment flow. Every sentence earns its place, and the information is well-structured and 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 tool has 6 optional parameters, an output schema (not shown), and no nested objects. The description explains what is returned (matching stocks ranked by market cap) and suggests pairing with another tool for more depth. However, it does not specify the format of the output or any result limits, though the output schema may cover that.

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 baseline is 3. The description adds meaning by explaining each parameter's role in the screening context (e.g., max_pe is maximum trailing P/E, sector is GICS with partial match). It also contextualizes payment_tx for re-calls after a 402, adding value beyond 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 clearly states it screens the tracked large-cap universe by specific filters (market cap, P/E, dividend yield, sector) and returns stocks ranked by market cap. It distinguishes from siblings by labeling itself a raw market-data filter and suggests pairing with another tool for a fundamentals-driven screen.

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 explicitly explains when to use (for raw market-data filter) and when not (for ranked fundamentals-driven screen, use financial-signals-mcp). It also details the payment flow, free allowance, and how to handle 402 errors, providing clear instructions for invocation.

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 provided, the description should disclose behavioral traits like auth requirements, rate limits, or any side effects. It only states the tool is free and gives usage context, but lacks details on safety or operational characteristics.

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 two sentences long, front-loaded with the core functionality and output details, followed by a concise usage note. Every sentence adds value with no unnecessary text.

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 the presence of an output schema, the description adequately covers the tool's purpose and output scope (11 sectors, multiple time periods, ranking). No further details are needed.

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 no parameters, and the schema coverage is 100%. The description correctly implies no input is needed, meeting the baseline expectation for a zero-parameter tool.

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 retrieves market sector performance for 11 GICS sectors via SPDR ETFs, ranked by today's move with multiple time frames. It distinguishes from sibling tools like quote or daily_brief by focusing specifically on sector performance.

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 provides clear use cases ('For rotation, breadth, and macro positioning at a glance') and marks the tool as free. However, it does not explicitly state when not to use this tool or list alternative tools for similar needs.

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