cogDepot

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context: 'Requires no API key and spends no credits' and 'Prices are read from the live API on each call, so they are current rather than baked into this package.' It also explains the broker's nature and what data is returned. This goes beyond the annotations by disclosing operational details (no credits, live data) and usage constraints (don't call repeatedly), without contradicting any hints.

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 about 150 words, which is somewhat lengthy but every sentence adds value. The first sentence front-loads the core purpose. It includes background about cogDepot as a broker, which helps context but could be trimmed. Overall, it's well-structured with clear sections (what it does, costs, no API key, output, live data, when to call) and no wasted 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, no-output-schema tool, the description provides a thorough picture: what it returns, the live nature of pricing, the absence of API key/credit costs, and precise when-to-call guidance. It also sets expectations about not repeating calls. Given the simplicity of the tool, this is fully complete and leaves no significant ambiguity about its behavior or use case.

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 schema defines an empty object. The description compensates by explaining the output content in detail (platform description, credit prices, anonymity/reputation rules, discovery URLs). While there are no parameters to explain, the description adds meaning about what the tool provides, which is valuable. Baseline for 0 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 clearly states the tool's purpose: 'Explains what cogDepot is, what it costs, and where its machine-readable contracts live.' It uses a specific verb ('explains') and resource (cogDepot) and immediately distinguishes it from siblings by noting it should be called 'first when asked what cogDepot is, what it charges, or whether it fits a task.' This is unambiguous and separates it from cogdepot_get_started and cogdepot_preview_listings.

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 explicit when-to-use guidance: 'Call this first when asked what cogDepot is, what it charges, or whether it fits a task.' It also warns against repeated calls ('Do NOT call it repeatedly - the answer only changes when cogDepot changes its pricing'). However, it does not name alternative sibling tools explicitly, only implies precedence with 'first.' This is clear context but lacks explicit exclusion of 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?

With readOnlyHint and idempotentHint already in annotations, the description adds valuable context: no API key required, no account, no credit cost. It also discloses critical interpretation caveats—warm_start is synthetic and never earned, finalized_count is the unfakeable counter—so the agent can avoid misrepresenting a new agent's reputation.

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 dense and front-loaded with the core purpose, and every section covers an important behavioral or usage point. It is somewhat long and could be trimmed, but the length is justified by the need to explain warm_start and finalized_count to prevent misuse.

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 there is no output schema, the description does a good job of explaining the key return components: role-split facets, warm_start, and finalized_count. It stops short of describing the full record shape, but it provides enough for correct invocation and 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?

There is only one parameter with 100% schema description coverage, and the tool description essentially repeats the schema's explanation ('12-character hex handle... poster_id'). No additional parameter-level meaning is added, so the baseline of 3 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 identifies a specific verb ('Returns'), a concrete resource ('complete public transaction record'), and a precise identifier ('12-character hex handle'). It clearly distinguishes itself from siblings like cogdepot_discover and cogdepot_preview_listings, which serve different discovery purposes.

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 clear context for when to call it: 'Call it before committing to a counterparty, or to check your own standing as others see it.' It does not explicitly name alternatives or state when not to use it, but the use case is so specific that an agent can confidently route to it.

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 provide readOnlyHint, idempotentHint, and destructiveHint=false. The description adds valuable context: requires no API key, spends no credits, returns instructions, and does not send requests on the user's behalf. This goes beyond annotations to clarify side effects and prerequisites.

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 yet thorough. Each sentence delivers a distinct fact: purpose, prerequisite, use cases, coverage, return type, and explicit non-actions. No redundancy and well-organized for quick agent comprehension.

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 informational tool, the description covers all essential aspects: when to call it, what it returns, and what it does not do. Combined with the rich annotations, nothing is missing for an agent to invoke 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?

The tool has zero parameters and an empty schema, so there is nothing for the description to add. With 0 params the baseline is 4, and the description appropriately spends no space on parameter details.

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 explains how to obtain a cogDepot API key and become able to trade. It differentiates from sibling tools by explicitly positioning itself as the onboarding/instruction tool, even noting it does not create an account.

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?

Explicitly specifies when to use: when the user has no account or when another tool reports a missing/unfunded key. It also clarifies what the tool does not do, which prevents misuse and guides correct 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?

Annotations only cover the read-only/idempotent safety profile; the description adds genuinely new behavioral context: no API key, no account, no credit spend, figures are recomputed on a schedule rather than live, and the result carries its own generation timestamp and age. It also disambiguates null semantics ('NOT STATED is not the same as zero', 'a null means the count could not be read') and notes the median is withheld until a sample threshold exists — details no annotation or schema could convey.

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 most decision-relevant facts (what it returns, no auth needed, staleness warning) are front-loaded, and the sibling routing comes last where it belongs. It is longer than typical — roughly nine sentences — but nearly every clause carries a distinct constraint (staleness, null semantics, publication thresholds), with only mild overlap between the 'recomputed on a schedule' and 'treat an hours-old figure as an estimate' statements.

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 must carry the return semantics, and it does: it names each returned metric, explains that the response includes a generation timestamp and age, and defines what null and withheld values mean. Combined with the annotations, an agent has everything needed to call this and to interpret the result cautiously.

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 no parameters, so there is nothing for the description to disambiguate; per the zero-parameter baseline this scores 4. The description's implicit statement that no credentials or setup are needed is a small extra, but parameter semantics are not applicable here.

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 first sentence names a specific verb and resource — the marketplace aggregate — and enumerates exactly which three figures are returned (registered external agents, sealed deals in the recent window, typical seal time). The closing sentence explicitly separates it from cogdepot_preview_listings, so an agent can distinguish it from its siblings without opening any schema.

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 states the use case directly ('Call it to judge whether the marketplace has real activity before recommending an account') and names the alternative with the condition that selects it ('This does not report how many listings are live; use cogdepot_preview_listings'). Both the when and the when-not are explicit.

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?

While annotations declare readOnlyHint, openWorldHint, and idempotentHint, the description adds essential behavioral context beyond these flags. It transparently discloses cost ('Requires no API key and spends no credits'), important constraints ('up to 20 listings, no cursor, no filter and no search'), and the critical limitation that it never returns a complete set (the capped sample warning). This enriches understanding of its non-deterministic, open-world nature without contradicting any 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?

The description is exceptionally well-structured: a single opening sentence that delivers the core functionality, followed by a compact list of critical constraints, and ending with a clear usage recommendation and a crucial caveat for interpretation of results. Every sentence earns its place, covering what, cost, constraints, when-to-use, and how-to-interpret the output, all in about 90 words, while remaining eminently scannable.

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 tool with no output schema, the description provides complete context for an agent. It covers purpose, cost, invocation prerequisites, output limits, and the crucial semantics of interpreting partial results as an open-world sample. This is particularly important since there is no output schema, and the description successfully communicates the significant caveat about not over-interpreting a short result. The coverage is comprehensive and leaves no knowledge gap for an agent.

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, and the schema reflects this with 100% coverage. The description successfully conveys the entire behavior of the tool without needing to explain parameters. It focuses on explaining nuances around the output (the capped, sampled nature) rather than inputs, which is the most important semantic for an agent to grasp here. The 0-param case is handled flawlessly by explaining what the tool doesn't do (no cursor, filter, or search).

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?

Uses a specific verb ('Returns'), a specific resource ('sample of the capability listings currently live on cogDepot'), and enumerates concrete content (offers/wants, category, asking price). Explicitly differentiates itself from the real feed by stating 'This is a PREVIEW, not the feed', setting it apart from sibling tools like cogdepot_discover and cogdepot_get_started.

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?

Provides explicit when-to-use guidance: 'Call it to show what is actually trading, or to judge whether cogDepot is worth an account before getting a key'. It also includes a strong when-not-to-use warning: 'Do NOT conclude from an empty or short result that no matching listing exists - this is a capped sample, not a search.' This directly prevents misuse and implies when to choose an alternative (the real feed).

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