strategy-lab

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

No annotations are provided, so the description carries full responsibility. It discloses the simulated/paper-mode nature of positions and the 'published track record' caveat, which is critical for correct interpretation. It does not mention side effects or return format, but those are less critical for a read-only state getter.

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, front-loaded with the data contents and followed by a crucial caveat. Every word earns its place; there is no redundancy or filler.

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 tool with no output schema, the description fully covers what data is included and how to interpret it (paper mode, track record). No further information is needed for an agent to correctly invoke and use this 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 tool has zero parameters, so the baseline is 4. The description does not need to explain parameters, and the schema is trivially complete.

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 reads the agent's live state, enumerating specific contents (treasury, open positions, recent trades, reasoning). The title and description together distinguish this from sibling tools like get_strategy or get_certification_gate.

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 important context about execution being in paper mode, implying the tool should be used as a track record rather than a real portfolio. However, it does not explicitly name alternatives or state when not to use it, stopping 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.

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

No annotations are provided, so the description carries the burden. It adds important interpretive context—clarifying that certification is a statement about a distribution, not a prediction—which goes beyond simply retrieving thresholds.

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, each earning its place: the first defines the tool's output, the second provides critical context. No redundancy or unnecessary detail.

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 simplicity (no parameters, no output schema), the description fully covers what the tool does and why it matters, including an important caveat about interpretation.

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 the schema confirms this. The description adds no parameter details, but none are needed; the baseline for zero params is 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 states the tool returns the exact certification thresholds for strategies, with a clear focus on what a pass means. This distinguishes it from siblings like get_strategy or list_strategies, which deal with other aspects.

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 says to read this before interpreting any certified strategy, giving a concrete use case. It doesn't name alternatives, but the guidance is clear and actionable.

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 the specific information returned (counts, balance, funding, cost) but does not explicitly state read-only nature, authentication requirements, or potential side effects. The lack of any warning about cost or access is a minor gap.

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 sentence that front-loads the key metrics: counts, balance, remaining runs, cost per run. Every word contributes to understanding the tool's output, with no 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 parameterless summary tool with no output schema, the description lists the main outputs and is largely adequate. However, it does not mention any caveats, return format, or typical use scenarios, which would make it fully complete. Still, the simplicity of the tool makes this sufficient.

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 0 parameters, so the schema is empty and schema description coverage is 100%. Per rubric, 0 params gives a baseline of 4. The description adds no parameter-level detail, but none is needed, and the listed output metrics give sufficient context for invocation.

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 lists specific outputs: counts by status, testing pool balance, remaining funded runs, and cost per run. This is a precise verb+resource+scope, and it distinguishes itself from sibling tools like get_agent_state or get_strategy by focusing on lab-level summary metrics.

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 when-to-use or alternative guidance is provided. The description implies use when a summary of lab metrics is needed, but it does not mention when to avoid this tool or direct users to siblings, leaving some ambiguity.

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 burden of disclosing behavior. It goes beyond a simple read by explaining the significance of the PRNG seed and the falsifiability aspect, which is valuable context about how the output can be reproduced. It clearly implies read-only behavior via 'Read' and 'get' and lists exactly what is returned.

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 with no fluff. The first sentence quickly enumerates the output contents; the second explains the key behavioral nuance about the seed. Every word earns its place and is front-loaded with the core purpose.

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 must explain return values, and it does so thoroughly by listing all included components. It also conveys the unique value of the seed. Minor gaps like error handling or how to obtain an id are not covered, but for a simple read tool this is nearly complete.

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% and the single parameter 'id' is minimally described as 'Strategy id.' The description does not add further semantics about the id format or how to obtain it, but since the schema already documents it, the baseline of 3 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 states a specific verb ('get') and resource ('single strategy') and enumerates the exact contents (parameters, thesis, verdict, gate checks, test runs with seeds). It clearly distinguishes from siblings like list_strategies or get_certification_gate by focusing on full detail for one strategy.

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 when to use this tool—when full detail for a single strategy is needed—and the sibling list_strategies suggests an alternative for summaries. However, it does not explicitly state exclusions or name alternatives, so it is clear but lacks direct comparison.

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 burden. It discloses the return format (certification rollup metrics such as run count, median PnL, ruin rate), which is valuable. However, it does not mention pagination behavior, how the limit parameter affects results, or explicitly confirm it is a read-only 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?

Two concise sentences, front-loaded with the purpose and filter options, followed by a clear list of return metrics. Every sentence contributes meaningful information with no 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 list tool without an output schema, the description provides the essential return metrics and filtering options. It lacks details on sorting and limit semantics, but the schema provides some structure (enums, defaults). Overall, it is sufficiently informative for typical use.

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% (only kind and status have descriptions). The description adds semantic value by stating that kind and status are filters, but it does not explain the sort or limit parameters, which also lack schema descriptions. Thus it partially compensates for the gaps.

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 lists strategies and specifies filterable attributes (kind, status), distinguishing it from siblings like get_strategy. It also explicitly enumerates the return metrics, making the tool's purpose 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 implies when to use it (listing multiple strategies with optional filters) and provides clear context for filtering by kind and status. It does not explicitly contrast it with alternatives like get_strategy, but the listing focus is evident from the name and description.

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