sygnldata — market intelligence for trading agents

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

No annotations are provided, so the description carries full burden. It discloses a $5.00 cost and the format for trades_csv, but omits side effects, rate limits, auth requirements, or the exact output format beyond 'verdict + grade'.

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 three concise sentences. The purpose is front-loaded, and each sentence adds distinct value: purpose, components, and input format. No redundancy or fluff.

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 lack of output schema and annotations, the description adequately covers the main input (trades_csv) and broad output (verdict+grade). However, it leaves three optional parameters unexplained and does not describe the return type in detail.

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 0%. The description adds meaning only for trades_csv (specifying column format). Three parameters (preset, n_trials, payment_signature) are left unexplained, so the description does not compensate for the lack of schema descriptions.

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 performs a 'forensic audit of a backtest trade ledger' and lists specific checks (impossible-fill detection, cost-adjusted expectancy, overfitting checks) and outputs (verdict + grade). This distinguishes it from sibling tools like check_bar_quality or estimate_execution_cost.

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 implies usage after running a backtest but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites. The context is implicit.

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 carries the full burden. It mentions what the tool detects (impossible bars, bad prints, etc.) and suggests a cost ($0.05), but does not explicitly state whether the tool is read-only or has side effects. It implies it is an analysis tool, but more explicit behavioral disclosure would be better.

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 extremely concise: two sentences with no filler. The first sentence immediately states the purpose, and the second provides key details. Every word 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 input format and purpose but does not describe the output format or what the tool returns. Given the lack of an output schema, this is a notable gap. A user would not know what to expect after calling 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?

The schema has 0% description coverage, so the description must compensate. It explains the 'bars' parameter format and row limits (5..100000 rows). The 'payment_signature' parameter is not explained, but it is optional with a default, and the description mentions a cost, providing partial context.

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's purpose: 'Forensic QC on YOUR OHLCV bars before you backtest on them.' It specifies the resource (OHLCV bars) and distinguishes from sibling tools like audit_backtest, which focuses on backtest auditing, and get_pricing, which retrieves price data.

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 implies use before backtesting ('before you backtest'), providing clear context. It does not explicitly state when not to use or list alternatives, but the sibling tools are sufficiently distinct so that confusion is 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?

No annotations are provided, so the description bears full burden. It discloses calibration methodology and order type constraints, but does not specify idempotency, data freshness, or error handling. The description adds useful but incomplete behavioral context.

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 front-loaded with the core purpose. The single sentence structure plus a detail line is efficient with no redundant 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?

Given 5 parameters, no output schema, and no annotations, the description is incomplete. It omits explanations for most parameters and does not describe the return format or edge cases. The tool cannot be used safely without additional context.

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. It only adds meaning for the 'order_type' parameter by listing allowed values (limit_nbbo | market). Other parameters like side, symbol, notional_usd, and payment_signature receive no explanation 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 the tool estimates realistic execution cost in bps for an order, including calibration details like SPY/QQQ 1.5bps floor and square-root size impact. It distinguishes from sibling tools which focus on audit, pricing, or regime data.

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 implies usage for cost estimation but does not explicitly state when to use versus alternatives like get_pricing or audit_backtest. No exclusion criteria or prerequisites are mentioned.

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 burden. It discloses the tool is 'FREE' and lists the data it provides (price list, payment network, payTo address). However, it does not explicitly state whether it is read-only or if any side effects exist, though it is implicitly a read operation.

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 a single, front-loaded sentence that efficiently conveys the tool's purpose and key behavioral trait (FREE) without any unnecessary words.

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 fully defines what the tool returns (price list, payment network, payTo address) for all paid tools. With no output schema and no parameters, it provides adequate information for an agent to understand the tool's output.

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?

There are no parameters, and schema coverage is 100%. The description adds no parameter information since none exist, meeting the baseline expectation.

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 price list, payment network, and payTo address for all paid tools. The verb is implied (get), resource is pricing, and it distinguishes from sibling tools like audit_backtest or get_regime_current.

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 is straightforward for a tool with no parameters, implying its use for retrieving pricing info. It lacks explicit when-not-to-use or alternatives, but the context is clear enough given the sibling tool names.

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 the description carries full burden. It discloses that VOLATILE predicts ~2x forward volatility with ~90% persistence, providing valuable behavioral insight. However, it does not address parameter behavior or 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?

Two brief paragraphs: first gives the core output, second adds statistical context. No wasted words, front-loaded with key 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?

Explains output meaning well but omits explanation of the input parameter. No output schema, but description partially compensates with interpretation guidance.

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%. The description does not mention the only parameter 'payment_signature' at all, leaving its purpose and usage completely unexplained.

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 provides 'Live market regime' with outputs STABLE/VOLATILE, confidence, and position scalar. It distinguishes from siblings like get_regime_history and get_regime_sample by emphasizing 'live' and 'current'.

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?

Explicitly states 'Use for position sizing / risk gating, NOT direction.' This gives clear usage boundaries. Does not name alternative tools but effectively guides when to use and when not to.

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?

Without annotations, the description discloses important behavioral traits: cadence (5-min), data range (since 2026-02), row count (417k+), and cost ($0.02). This helps agent understand resource implications.

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, highly concise. No wasted words. Front-loaded with purpose and key constraints.

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 4 parameters, the description covers core functionality, key constraints, cost, and data volume. Missing payment_signature explanation and return format, but adequate 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?

Clarifies that start/end are ISO timestamps and limit <=10000, but does not mention the payment_signature parameter at all. With 0% schema coverage, more parameter details would be beneficial.

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 'historical regime snapshots' with specific cadence and data volume. It distinguishes from sibling tools like get_regime_current and get_regime_sample by focusing on history.

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 practical usage guidance: ISO timestamps for start/end, limit constraint (<=10000). Implicitly indicates when to use (for historical data) but does not explicitly contrast with 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?

Discloses key traits: free, 24-hour delay, and being a sample. No annotations are provided, so the description carries the full burden. It effectively communicates the tool's non-real-time, read-only nature.

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?

Single sentence that is front-loaded with key information (FREE, 24h-delayed, market regime snapshot, taste). Every word is necessary, no wasted 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?

Provides enough for a simple tool with no parameters, but lacks detail on what the snapshot contains (e.g., which regime states). Given sibling tools, more specificity would help distinguish the output format.

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?

No parameters exist, so the baseline is 4. The description adds no parameter information, which is appropriate given 100% schema coverage and zero parameters.

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 it's a 24h-delayed market regime snapshot, using 'get' implied and 'sample' to indicate a free taste. It differentiates from siblings like get_regime_current and get_regime_history by noting it's a sample of the paid feed.

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?

Implies usage as a free preview, but lacks explicit when-to-use or when-not-to-use guidance compared to sibling tools. Does not state alternatives or prerequisites.

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