SCRIPTMASTERLABS — Quant Terminal

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 does disclose important behavioral context: it is a paid tool costing $0.05 USDC via x402 on Base. That pricing/payment detail is genuinely useful. It does not cover auth requirements, rate limits, or data-source limitations.

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 sentence, front-loaded with the cost/payment method, followed by the core function and its output. No wasted 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 explains the return values (what happened at 5/10/20 sessions later), which helps since there is no output schema. But for a 3-parameter tool with 0% schema coverage and no annotations, the undefined parameters leave gaps an agent needs filled.

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% across 3 parameters (symbol, window, universe). The description vaguely implies 'window' via 'latest window' but explains nothing about symbol, the window format, or the self/pair enum values. It fails to compensate for the low schema coverage.

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: find past windows whose daily return shape best matches the latest window, then report outcomes at 5/10/20 sessions. Clear what it does. It does not differentiate itself from sibling tools like mirror_projection or quant_snapshot, which appear related.

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?

Usage is implied by the description ('best matches the latest window'), so the agent can infer this is a historical-analog lookup. However, there is no explicit when-to-use versus siblings, no exclusions, and no prerequisites 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?

With no annotations, the description carries the full behavioral burden; it usefully discloses the paid cost, x402/Base payment rail, output nature, and non-forecast caveat. However, it does not explicitly state read-only/no-side-effect behavior, rate limits, or error handling.

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 compact and front-loaded: payment, operation, return shape, and caveat each appear in a short, purposeful sentence. There is no redundant or filler language.

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 core projection concept and paid access requirement are covered, but with no output schema, no annotations, and only 50% parameter description coverage, important details such as horizon semantics and sibling-tool routing remain unclear.

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 50%, and the description adds conceptual meaning for the ticker, past window, and example date. But it never explains the horizon parameter, and symbol is only indirectly described, so it does not fully compensate for the coverage gap.

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 operation: walking a ticker's latest close forward through the real session-by-session returns of a past window. It clearly frames the result as a hypothetical analog rather than a forecast, but it does not explicitly distinguish itself from sibling tools such as analog_scan.

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?

Usage is implied by the described operation and example, but there is no explicit guidance on when to use this tool versus analog_scan or quant_snapshot. It also lacks when-not-to-use conditions or prerequisite details beyond the paid x402 note.

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 key traits: evidence is 'actual' bars, the x402 price is consumed, and no orders are executed. What it omits is material for an agent: whether the call is read-only, whether it incurs the x402 charge itself, what happens on insufficient evidence, and whether WAIT is a valid return rather than an error.

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 with the substance front-loaded; the exclusions and sibling pointer are packed efficiently. The dense noun stack ('full-terminal x402 price', 'observed structure and input receipt') costs some readability but nothing is padding.

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 useful work by listing the return artifacts (bars, typed reasons, structure, receipt) and the refusal boundary. It still leaves the one input undefined and does not clarify the cost/auth implication of the x402 price it depends on, which is significant for a paid decision endpoint.

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 is one required parameter (symbol) with 0% schema description coverage, and the description never mentions it. An agent gets no guidance on ticker format, market/exchange qualification, or case sensitivity.

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 concrete outputs (daily/hourly bars, WAIT/SETUP reasons, observed structure, input receipt) and frames the tool as a decision workspace rather than a scanner. However, 'evidence-gated equity decision workspace' is opaque jargon and the verb+resource pair is never stated plainly, so an agent must infer that this returns an analysis/decision for a symbol.

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?

It routes the agent to x402_contract for current pricing terms and gives a negative boundary ('No order execution or profit probability'), which is genuinely useful. It never states when to prefer this over quant_snapshot or mirror_projection, and no prerequisite for obtaining the x402 price is spelled out.

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 must carry the full behavioral burden. It discloses the cost ($0.02 USDC via x402, Base) and data sources (Tradier, Massive/Polygon, Alpaca), which are important. However, it omits rate limits, authentication details beyond payment, error handling, and whether the operation is read-only (though implied).

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, information-dense sentence with no wasted words. The cost and core functionality are front-loaded, and the parenthetical list is 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 no output schema and no annotations, the description should ideally explain the return structure and more behavioral details. It lists the data points but does not describe the output format or error conditions, leaving gaps for an agent to call it 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 0% for the single 'symbol' parameter. The description adds that it is 'for a US ticker', clarifying the expected value type, but does not specify format (e.g., 'AAPL' vs 'AAPL.US') or constraints. It partially compensates but leaves ambiguity.

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 resource (US ticker) and enumerates the data returned (live quote, completed-session levels, cross-check), making the tool's function clear. However, it does not explicitly differentiate from sibling tools like analog_scan or mirror_projection, so it falls 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?

No guidance is provided on when to use this tool versus alternatives. It mentions the tool is paid and for US tickers, but does not state when to choose it over siblings or any 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?

Since there are no annotations, the description carries the full burden of behavioral disclosure. It describes the complex payment gating mechanism (402 error and subsequent required retry logic) which is critical behavioral information.

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 technical description is dense but well-structured, segmenting free vs. paid usage in a manner that guides the agent effectively without unnecessary 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?

For a zero-parameter contract tool, the description is maximally complete, covering the specific operational requirements (payment, network, URL access) needed to use or troubleshoot the paid endpoints.

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 100% schema coverage. Baseline score for 0 parameters applies, as the description is not required to define inputs.

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 defines the scope of the tool—providing contracts, pricing, and access mechanisms—distinguishing it as a meta-informational tool rather than an execution tool like its siblings.

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?

It provides explicit usage instructions, explaining that while free information is available, paid calls require a specific workflow: making the initial call to receive the HTTP 402 and then retrying with a PAYMENT-SIGNATURE.

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