outcometick

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

Annotations already cover read-only and open-world safety. The description adds valuable context beyond that: it is public (no obvious auth), the available window is limited to the most recent sold window, and the response includes queue busyness.

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 short sentences with the core question front-loaded, followed by the key limitation and output hint. No filler or 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 low-complexity tool with one parameter and no output schema, the description covers the basic purpose and some behavioral context. However, it omits parameter semantics and explicit usage guidance, leaving gaps an agent must infer.

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 venue parameter. The description says 'on a venue' but does not explain the meaning of the parameter or its enum values (polymarket, predict), so it fails to compensate for the missing schema documentation.

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 and scope: which days are backtestable on a venue, plus queue busyness. It is clear what the tool returns, but it does not explicitly differentiate itself from siblings like backtest_quote or coverage.

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 explicit when-to-use or when-not-to-use guidance. The note that only the most recent window is sold hints at a constraint but does not tell the agent when to choose this tool over 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 declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds meaningful context beyond that: the call has no side effects ('without submitting anything'), requires no authentication ('Public'), and states the pricing model explicitly.

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 short sentences, front-loaded with the core action and cost unit, then the public/no-submit facts, then the input-selection rule. No filler and nothing buried.

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 7-parameter tool with no output schema, the description covers the essential pricing semantics and range specification but leaves the interaction between 'intervals'/'language' and the credit cost unexplained, which is central to a quoting 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 coverage is 57%, and the description usefully clarifies the mutually exclusive date-range inputs ('either from/to or days') and defines 'days' as the most recent n archived days. It says nothing about how 'intervals' or 'language' affect the credit total, even though the schema hints that language changes how many market-days a run may hold.

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 ('Price') and resource ('backtest scope') with the unit defined ('1 credit = 1 market-day'), so an agent knows this computes a cost estimate. It does not explicitly differentiate itself from the sibling backtest_capacity, which likely covers a related capacity/cost question.

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?

'Without submitting anything' implies this is the pre-flight/dry-run call rather than an execution call, which is useful usage context. However, no sibling is named as an alternative and there are no explicit when-not conditions (e.g., when to use backtest_capacity instead).

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 cover the safety profile (readOnlyHint, openWorldHint), so the bar is lower; the description still adds genuine context by disclosing cost/auth ('Free, no key'), validator parity with the backtest queue, and the default time window. It omits what happens on validation failure and whether pricing is a simulation or a commitment.

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, front-loaded with the core action, and every clause carries information an agent needs (validator parity, cost, date-argument rules, default). No filler or restatement of the name.

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?

There is no output schema, so the description should carry return-value expectations. It says it 'validates' and 'prices' but never states what comes back (validation errors vs. a price figure), nor what the response looks like when a strategy fails validation — a meaningful gap for a tool whose primary job is validation.

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 67%, so the schema documents most fields, but the description adds meaning the schema lacks: the from/to-vs-days mutual exclusivity, the 7-day default, and that files are 'sent as contents'. venue and assets get no added semantic color, but their enum/example descriptions in the schema are adequate.

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 two specific verbs (validate, price) and the exact resources (manifest.json + source files, contents-based), plus the scope qualifier. The phrase 'the exact validator the backtest queue runs' is a concrete distinguishing detail. It does not, however, explicitly differentiate itself from siblings like backtest_quote, and 'price it' overlaps with that sibling's apparent domain.

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?

Gives real invocation guidance: 'Free, no key' removes auth uncertainty, 'Give either from/to or days' defines a mutually exclusive parameter choice, and the default fallback (most recent 7 days) is spelled out. No explicit when-not-to-use or named alternative (e.g. backtest_quote for pure pricing) is offered.

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 readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds genuinely useful context beyond them — that the endpoint is public and needs no API key — but says nothing about response shape, size or any rate limits on a public open-world call.

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 compact fragments, front-loaded with the resource and scope, with the access constraint last. Every clause carries information; only the missing verb slightly weakens the structure.

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 carries the burden of saying what comes back, and it does enumerate the three content categories (assets, datasets, day range). It does not describe the response format or how venues are keyed, so it is adequate but not fully self-sufficient for a discovery call.

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 there is nothing to document and the baseline of 4 applies. The description correctly implies no filtering input is required or accepted.

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 precisely — a per-venue inventory of what the archive holds (assets, datasets, day range) — so an agent knows this is a metadata/discovery call rather than a backtest or strategy check. It lacks an explicit verb ('returns'/'lists'), which keeps it just short of a 5, but the content is unambiguous and clearly distinct from the sibling tools.

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 call this versus backtest_capacity, backtest_quote, check_strategy or plans. 'Public, no key' is an access note, not routing guidance, so the agent must infer that this is the discovery step before using the other tools.

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 declare readOnlyHint and openWorldHint, and the description adds information they do not cover: no API key or authentication is required and the prices returned are live rather than cached. That is genuine added behavioral value, though it says nothing about rate limits, pagination, or result size.

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 short fragments, zero filler, and the core content ('plans and their live prices') is front-loaded before the access note. Nothing to trim.

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 public listing with no output schema, the description covers what is returned and the auth posture, which is most of what an agent needs. It could still note response shape (currency, plan tiers) but the gap is minor.

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 there are no parameter semantics to explain; the baseline for a no-param tool is 4. The description correctly implies the call is unfiltered.

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 and its payload ('subscription plans and their live prices'), so an agent knows what comes back, but there is no verb and no scope statement. Sibling tools (backtest_*, coverage, check_strategy) don't overlap, so disambiguation pressure is low, yet the phrasing 'Data subscription plans' is slightly ambiguous as to whether it is a catalog listing or a plan-management surface.

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?

'Public, no key' tells the agent it can call this without credentials, which is useful invocation context, but it never says when to use this versus the sibling tools or in what workflow it belongs. Usage is only implied.

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