Free Agent Economy Lab

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

Annotations already indicate readOnly and non-destructive behavior; the description reinforces this by stating 'Never moves funds' and adds behavioral context by listing the allocation gates (audit, risk, liquidity, etc.), providing transparency beyond 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?

Two efficient sentences, no fluff, front-loaded with the core purpose, and the second sentence adds critical safety context. Every word 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?

Despite having 7 parameters and no output schema, the description omits details on return values, venue object structure, and parameter mapping to gates. Given the tool's complexity, more context is needed for effective 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?

With 0% schema description coverage, the description carries the full burden for parameter meanings, but it only implicitly refers to venues and capital without explaining optional parameters like max_risk_score or max_credible_apy. The parameter names are somewhat self-explanatory, but the description adds minimal semantic detail.

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 allocates paper capital across 1-10 yield venues using multiple gates and explicitly states it never moves funds, distinguishing it from sibling tools like compare_providers and verify_outcome.

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 planning/allocation simulation but does not explicitly state when to use this tool over compare_providers or verify_outcome. The 'Never moves funds' statement provides some guidance, but it lacks explicit when-not-to-use instructions.

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 indicate read-only, non-destructive behavior. The description adds valuable detail about the ranking method (success, quality, cost, sparse-sample penalty), which is beyond what annotations provide. However, it does not explain the output format or behavior for edge cases.

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, well-structured sentence that front-loads the verb 'Rank' and includes key criteria. Every word earns its place, and there is 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?

Given the tool's moderate complexity (2 parameters, no output schema), the description is adequate but incomplete. It fails to explain the ranking output (e.g., format, tie-breaking) and the meaning of the 'sparse-sample penalty', which is critical for correct 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 description coverage is 0%, so the description must explain parameters. It implicitly covers 'receipts' (supplied outcome receipts) but entirely omits 'minimum_samples', which is a required integer with a default. This gap is critical for a tool with only two 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?

The description clearly states the tool ranks providers using specific criteria (success, quality, cost, sparse-sample penalty). It distinguishes from siblings (allocate_treasury_paper, verify_outcome) which have different purposes. However, the term 'outcome receipts' is not defined, causing slight ambiguity.

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 gives no explicit guidance on when to use this tool versus siblings, nor does it mention when not to use it. Usage context is only implied; no alternatives or exclusions 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. Description adds that it checks delivery, spend, and quality requirements, which is consistent but not additional behavioral context. No contradictions.

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, no unnecessary words. Directly conveys the 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 one parameter (nested object, no output schema), the description covers the high-level purpose but lacks details on input format and expected output. Annotations help but the description could elaborate on what constitutes success/failure.

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 parameter 'receipt' is an object with no inner documentation. Description mentions 'supplied agent-outcome-receipt/0.1' which hints at the format but does not explain required fields or structure. Insufficient compensation for 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?

Description clearly states verb 'Check whether' and specific resource 'agent-outcome-receipt/0.1'. Differentiates from unrelated siblings allocate_treasury_paper and compare_providers.

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 alternatives provided. The description implies a verification use case but lacks guidance on when to choose this tool over others. Siblings are different enough that confusion is unlikely, but still no usage context.

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