trades-runtime

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

With no annotations provided, the description carries the full disclosure burden and does notable work: it declares the operation read-only, states the data lives only on the operator machine, asserts the Worker holds no tenant data, and admits it was not tested against a live tenant. That provenance and safety context is genuinely beyond structured fields, though it omits any note on data freshness, size, or caching.

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 core purpose is front-loaded, but the middle sentence is a bloated enumeration of internal modules and seventeen named vendor peers that consumes most of the description. The list conveys content, yet the same information would be better served by the response itself, and it crowds out usage guidance.

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?

No output schema exists, so the description must characterize the return value, and it does describe the local_package structure and the peer entries' fields (mode, mappingConfidence) reasonably well. It stops short of a full shape description, but the disclosure of scope, safety, and provenance is sufficient for a zero-parameter read.

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 the schema (empty object, additionalProperties false) already fully defines the call and there is nothing for the description to compensate for. Baseline 4 applies.

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 a specific resource ('cite.json for Trades-Runtime') and enumerates its contents (local_package modules plus platform peers with mode/mappingConfidence), so an agent knows exactly what it retrieves. It does not, however, explicitly distinguish itself from the sibling tools (health, skill, stats), leaving the agent to infer the difference from the resource name alone.

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 tool versus trades_runtime_health, trades_runtime_skill, or trades_runtime_stats, and no prerequisites or exclusions. 'Public' and 'Read-only' imply a safe inspection call, but the agent receives no routing guidance at all.

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 the key traits: read-only, does not increment counters, holds no tenant data, never writes. However, it omits auth requirements and what the health response contains, and the tangent about writes occurring in the local runtime on the operator machine describes a different component, which adds confusion rather than clarity.

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 lead ('Trades-Runtime giveaway health. Read-only.') is well front-loaded, but the following three sentences restate the same no-write idea repeatedly ('does not increment counters', 'never writes', 'writes exist only in the local runtime'). Roughly half the text is redundant.

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 diagnostic tool this is close to sufficient — side effects are covered — but it never says what the health check returns or when a failing result should prompt action, and there is no output schema to fill that gap.

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 zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. No misleading parameter claims are made.

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 phrase 'Trades-Runtime giveaway health' identifies a resource (the trades-runtime giveaway) and an implied operation (health check), but never states the verb or what 'health' concretely reports. It also makes no attempt to distinguish itself from siblings trades_runtime_cite, trades_runtime_skill, and trades_runtime_stats.

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 tool versus the three sibling runtime tools, no prerequisites, and no exclusions. The agent must infer from the name alone that this is a diagnostic/status check.

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 clearly states 'Read-only' and describes the markdown's content areas (modules, platform peers, mapping confidence), which is useful. However, it omits permissions, rate limits, and the exact response format, leaving meaningful gaps for a retrieval tool.

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 with no filler. It is slightly dense and lacks a clear verb, but every phrase contributes to describing the returned artifact.

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 retrieval tool with no annotations or output schema, the description gives a reasonable content overview but does not explain how the markdown is structured or when to choose this tool over its siblings. It is minimally adequate but leaves selection and return-format questions open.

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 the baseline score of 4 applies. The schema is fully described and the description does not need to compensate for parameter 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 identifies the artifact as an 'Agent skill markdown for the public giveaway Worker' and lists the content it includes, but it uses a noun phrase with no action verb. It does not distinguish this tool from its siblings (cite, health, stats), leaving the agent to infer whether it fetches, generates, or renders the markdown.

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 guidance on when to use this tool versus the sibling tools, nor any prerequisites or conditions. The only contextual cue is 'Read-only,' which implies it is safe to call but does not help with tool selection.

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 behavioral disclosure. It states 'Read-only' and 'Does not increment counters,' which are important safety guarantees. It does not describe the return format or any error behavior, but for a simple read operation, the core behavioral traits are covered.

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 is front-loaded with the core action ('Honest KV view/download counts') and then adds essential behavioral qualifiers. Every word earns its place; there is 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?

The tool has no output schema, so the description should explain what the return data looks like. It does not describe the shape of the counts (e.g., JSON structure, fields, or whether they are aggregated). While the operation is simple, an agent might need to know the output format to process it correctly. This gap prevents a higher score.

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 is empty. With no parameters to document, the baseline is 4. The description adds nothing about parameters (correctly), as none exist. It effectively compensates for the lack of a schema by providing context on what the tool measures.

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 precisely states the tool's function: 'view/download counts with human/bot split' for a KV store. This clearly distinguishes it from sibling tools (skill, health, cite) which serve different purposes. The verb and resource are concrete and unambiguous.

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 does not explicitly mention when to use this tool versus its siblings, nor does it state any exclusion conditions. However, the distinct focus on stats/logs implicitly signals it is for retrieving counts rather than for skill execution, health checks, or citation tasks. This is sufficient but not proactive.

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