Sputnik X Market

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

With no annotations provided, the description carries the full behavioral disclosure burden. It explicitly states read-only semantics, no mutation, fail-open behavior with mock fixtures when upstream is unreachable, and environment configuration requirements. This is unusually transparent and adds real operational context.

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 with no filler: first sentence states core purpose and output, second covers configuration/test mode, third confirms safety and failure behavior. Every sentence contributes actionable information and the most important identifying details are front-loaded.

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 moderate-complexity read tool with no annotations and no output schema, the description covers purpose, data source, configuration, failure mode, and safety. It lacks an explicit return-format example or error-behavior details, but the listed output fields and fail-open note make it sufficiently complete for reliable invocation.

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?

Input schema covers all four parameters with meaningful descriptions, so baseline is 3. The description adds some context around test_mode ('suitable for CI and demos', fail-open behavior) and frames ticker as commodity-exposed equities, but it does not significantly extend the schema's 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?

Description states a specific verb ('lookup') and resource ('Daloopa fundamentals for commodity-exposed equities'), lists concrete returned fields (revenue, opex, segment splits), and explicitly marks itself as read-only. This clearly distinguishes the tool from siblings like get_prices or mt_newswires_query.

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 clear context: it is for fundamentals of commodity-exposed equities, can be used without upstream credentials via test_mode, and is read-only. It does not explicitly name sibling alternatives or when-not-to-use conditions, but the usage context is strong enough for an agent to select it appropriately.

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?

Since no annotations are provided, the description carries the full behavioral disclosure burden. It does well by revealing update cadence (weekly, Monday 07:00 UTC), data recency (signals delayed 7 days from detection), access level (free/public), and the exact output fields. This adds meaningful context beyond the schema.

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 and front-loaded with the core purpose, then adds cadence, output fields, and access constraints. Every clause carries useful information and there is no redundant or filler language.

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 simple tool with two optional parameters and no output schema, the description covers the input basis, the returned fields, freshness, and access model. Minor gaps remain, such as confidence scale interpretation and whether 'limit' can exceed the implied top-5, but these are not critical for basic invocation.

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 100%, with both 'limit' and 'since' already documented including defaults and format. The description adds no parameter-specific semantics, so the baseline score of 3 is appropriate because the schema handles the heavy lifting.

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 identifies the resource: top-5 front-running signals based on a policy event and trade spike 30 days prior. It also lists the returned fields, giving a concrete sense of what the tool produces. It does not explicitly compare itself to siblings like prediction_signals or wave_signal, but the domain and output are specific enough to avoid major 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 implies when to use the tool: when the agent needs publicly available front-running signals, especially those delayed by 7 days and updated weekly. It provides useful access context ('FREE lead magnet, public') but does not state when not to use it or name alternative sibling tools for similar signal needs.

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 full behavioral burden. The verb 'List' and the word 'Discovery' imply a read-only, non-mutating operation, but the description does not explicitly state that there are no side effects, whether authentication is needed, or what kind of output shape is returned. These are minor gaps for a simple discovery tool, but the description could be more explicit.

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 no filler. The main action and resource are front-loaded, and the second sentence adds the discovery purpose. 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?

For a zero-parameter discovery tool with no output schema, the description adequately conveys what the tool lists and why an agent would use it. It does not spell out the exact return structure, but the categories mentioned ('data sources, dimensions, metrics, and operations') give enough context for an agent to understand what to expect.

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 coverage is 100% trivially, since there is no property surface to document. The baseline for 0 parameters is 4, and the description correctly focuses on the output categories rather than trying to explain non-existent 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 states a specific verb ('List'), a concrete resource ('Fusion Engine data sources, dimensions, metrics, and operations'), and the purpose of the tool ('Discovery tool for understanding what cross-source queries are possible'). This clearly distinguishes it from the sibling query tools by identifying it as a meta/capability tool rather than a data retrieval tool.

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 frames the tool as a 'Discovery tool for understanding what cross-source queries are possible,' which clearly implies using it when planning or choosing what queries to run. It does not explicitly name alternatives or state when not to use it, but the context is strong enough for an agent to infer appropriate usage.

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 behavioral disclosure burden. It does add useful context: EUR currency, in-stock filtering, and calculated price_per_kg. However, it does not explicitly state that the operation is read-only, nor does it clarify behavior when product_slug is provided vs omitted.

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 with no filler. The first sentence states the core action, and the second adds the output scope and currency. Every sentence 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?

For a simple three-parameter read tool with a fully described schema, the description gives essential return context (EUR, in-stock, price_per_kg). However, the lack of annotations, output schema, and sibling differentiation leaves some gaps around filtering behavior and response details.

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 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond what the schema already provides for slug, product_slug, and response_format.

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 action and resource: get current product prices, including the computed price_per_kg. It clearly identifies the tool's domain, though it does not explicitly differentiate it from siblings like search_products.

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 guidance on when to use this tool versus alternatives such as search_products. It only restates what the tool does without exclusions or routing hints.

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 provided, the description carries the full behavioral burden and does so well: it declares read-only semantics, names the underlying feed configuration, specifies the returned object fields, and discloses both test_mode behavior and automatic mock fallback when the feed is unreachable. This is strong transparency beyond the schema.

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 three sentences with no wasted words. It front-loads the core purpose, states usage context, and then covers behavior and fallback mechanics efficiently. Every sentence adds distinct value.

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 no output schema, the description explicitly lists the return fields {title, pubDate, link, summary, source}, making the tool's output predictable. It also covers configuration, filtering context via schema, test mode, and failure fallback, so an agent has enough context to select and invoke the tool 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?

Schema description coverage is 100%, so the schema already documents all parameters (limit, since, topic, test_mode). The description adds little parameter-specific meaning beyond mentioning `limit` and test_mode, but because the schema handles parameter semantics fully, a baseline 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 opens with 'MT Newswires commodity headlines (read-only)' and immediately specifies the tool's action: pulling a configured RSS or JSON feed and parsing news items. It clearly identifies the resource (MT Newswires feeds) and output shape, and distinguishes it from sibling price/signal/portfolio tools as a commodity-news ticker.

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 states 'Use as a low-latency news ticker for commodity-trader agents,' giving clear context for when this tool is appropriate. It does not explicitly name alternatives or state when not to use it, but its news-feed purpose is distinct enough among siblings that the usage guidance is reasonably complete.

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 provided, the description carries the full burden. It does add useful behavioral context by stating the data comes from a 'paper trading bot', implying simulation and no real-world trades, and it lists the data categories returned. However, it does not explicitly say the tool is read-only, describe side effects, or disclose data freshness or ordering behavior. It is not misleading, but it is only partially transparent.

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 tight sentence that front-loads the core identity and then lists the main data categories. Every word contributes meaning, with no filler, repetition, or unnecessary detail. It is appropriately concise for the tool's simple parameter surface.

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, and the description only gives broad categories rather than the actual shape of returned data. An agent cannot tell what a 'signal' object contains, whether the results are ordered, or how 'strategy performance' is structured. The absence of usage guidance and return-format details makes this incomplete for a tool that must be invoked correctly without further schema support.

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 100%, so the parameters are already documented in the schema. The description adds minor semantic mapping by using 'strategy performance', 'active trades', and 'signal feed' to mirror the view enum values, but it does not add new parameter-level details. Baseline 3 is appropriate given high 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?

The description clearly identifies the resource: prediction market signals from a Polymarket paper trading bot. It lists the three content areas (strategy performance, active trades, signal feed), which maps to the view parameter. It does not use an explicit verb like 'retrieve' or 'list', but the noun phrase is unambiguous and mentions Polymarket, which helps distinguish it from other signal-related siblings.

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 alternatives such as wave_signal, get_prices, or other market-data tools. No conditions, exclusions, or recommended use cases are stated. The agent must infer usage solely from the data-source description, with no explicit routing.

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 must carry behavioral disclosure. It adds one important behavior—output is constrained to safe columns, excluding cost_price/markup—which is not visible in the schema. However, it does not describe return shape, defaults, ordering, or error behavior, leaving meaningful gaps for a tool without an output schema.

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, front-loaded with the purpose and quickly adding the safety-column constraint. Every sentence contributes information; 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?

The tool has six parameters, no output schema, and no annotations, so the description needs to cover returns and defaults. It covers the safe-column behavior but omits response_format semantics, limit/default behavior, and the fact that category/name filtering happens through the search parameter rather than separate parameters. Adequate but with clear gaps.

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%, so the schema already documents all six parameters. The description restates filtering by type/category/name/in_stock status, but adds no syntax, precedence, or formatting detail beyond the schema; baseline 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 names a specific verb and resource ('Search products in a tenant catalog') and immediately states the key differentiating constraint: returns safe columns only and excludes cost_price/markup, which separates it from price-focused siblings like get_prices. The filter dimensions are enumerated, making the tool's scope 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?

Clear use context is provided: search a tenant's product catalog with the supported filters. It does not explicitly name alternatives or provide when-not-to-use conditions, so it falls short of a 5, but the context is sufficiently clear that an agent knows this is the product-search entry point.

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 full responsibility for behavioral disclosure. 'Browse' implies read-only, but the phrase 'agents can claim and complete' could be misread as actions performed by this tool rather than attributes of the bounties. Additionally, describing the tool as browsing 'open' bounties conflicts with the schema's status filter that also supports 'awarded' and 'expired', creating ambiguity about the actual scope.

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 conveys the core purpose, the object type, and the reward aspect efficiently, earning its place without being verbose.

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 simple list tool with no output schema, the description is mostly adequate: it tells the agent what kind of items will be returned. However, it does not clarify pagination or the default behavior of limit, and the 'open' ambiguity could lead an agent to underuse the status filter. Overall it is minimally complete but has clear gaps.

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 input schema already provides 100% coverage with descriptions for both limit and status, so the description does not need to add parameter details. It adds general context about USDC rewards, but no additional meaning about how limit or status behave, leaving this at baseline.

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 clear action and resource: 'Browse open agent bounties' with USDC rewards. It is reasonably specific, though the word 'open' can be misread as a status filter when the schema actually allows open, awarded, and expired statuses. It does not explicitly distinguish from siblings, but the sibling names are topically distinct enough that this is not a major issue.

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 clear context for why an agent would call this tool: to find bounties that can be claimed and completed for rewards. It does not explicitly list exclusions or alternative tools, but the sibling set (e.g., get_prices, daloopa_query) suggests this is the designated bounty-browsing tool, making the intended use fairly clear.

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 behavioral burden. It communicates that this is a browse/list operation rather than a purchase action, and that items are 'available for purchase' elsewhere or separately. It does not disclose details like pricing, authentication, or result shape, but for a read-only browse tool this is acceptable though minimal.

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, tight sentence with no filler. The key action and resource are front-loaded, and the clarifying purchase context is appended without unnecessary words.

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 simple browse tool with two optional parameters, the description plus complete schema is mostly sufficient. However, without an output schema or annotations, it does not specify what the returned insights look like or how the purchase flow works, which leaves some context missing.

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 input schema already documents both parameters (limit and category) with complete descriptions, so schema coverage is 100%. The description adds no additional parameter-level detail, which is fine because the schema fully covers the semantics.

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 uses a specific verb ('Browse') and resource ('marketplace insights from AI agents'), and adds the clarifying detail that these are analysis findings available for purchase. This distinguishes it from sibling tools like soul_profile or soul_bounties, though it does not explicitly name a sibling alternative.

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 the tool should be used when an agent wants to browse AI-agent insights available for purchase. It provides clear context but does not state when not to use it or name alternatives, leaving some routing to inference.

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 provided, the description carries the full burden of disclosing behavior, but it only states that the tool ranks agents by trust score and includes DNA summaries. It doesn't disclose whether this is a read-only operation, whether the leaderboard is real-time or cached, whether 'DNA summaries' means nested data structures with a comparison basis, or whether limits beyond 10/50 affect behavior. The description adds minimal behavioral context beyond the input schema and its own top-line purpose.

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, compact sentence with no filler. It front-loads the most critical information: what the resource is, the ranking metric, and the included data ('DNA summaries'). One could argue it could clarify 'DNA summaries,' but for an 11-word description, it's efficient and well-structured.

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 and no annotations, the description should explain what a caller receives (e.g., fields per agent, how DNA summaries are structured) and why this tool exists in context. The current text is a title-like statement, not a complete tool contract. The single optional parameter is well-documented, but the result shape and usage context are unresolved, making this inadequate as a standalone tool definition.

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 description for 'limit' is 100% covered, clearly stating the default (10) and maximum (50). The tool description mentions ranking agents by trust score, which loosely contextualizes the limit parameter as controlling the page size of that ranking, but it doesn't expand on returned format or edge cases. Since schema coverage is full, the baseline of 3 is appropriate; the description doesn't add significant parameter semantics beyond the schema.

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 ('agent trust leaderboard'), a verb ('ranked'), and the ordering criterion ('trust score'), with 'DNA summaries' hinting at included data. It distinguishes itself from sibling tools like soul_profile or soul_insights, which likely serve different purposes, though it doesn't explicitly contrast itself. The context signals confirm a very limited output, so the core purpose is clear.

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 a read-only listing use case but provides no explicit guidance on when to choose this over related tools like soul_bounties or soul_stack_feed. Specialized terms like 'trust score' and 'DNA summaries' are left undefined, and there's no mention of prerequisites or when this tool is the right choice versus alternatives. This is implied usage only, not explicit routing guidance.

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 of behavioral disclosure. It communicates a read-oriented action via 'Get' and previews the output facets, which is useful context. However, it does not disclose permission requirements, error behavior, or what 'behavioral DNA' and 'character model' concretely contain.

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 starts with the action and packs in the resource and return facets. There is no filler, and the em-dash structure keeps the purpose front-loaded without sacrificing 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?

For a simple one-required-parameter read tool, the definition is nearly complete: the call contract is clear and the expected output areas are named. The lack of an output schema leaves return-structure details slightly underspecified, which prevents a perfect 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 only parameter, agent_id, is fully documented in the schema with example values, and schema description coverage is 100%. The description adds no parameter-level guidance, so the baseline score 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 names a concrete operation ('Get') and a specific resource ('agent identity profile'), and enumerates the returned dimensions (trust score, behavioral DNA, character model). It does not explicitly differentiate from sibling tools like soul_insights or soul_verify, so it misses the top score.

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 a clear use case—use this when you need an agent's identity profile—but it never states when not to use it or names a sibling alternative. The usage guidance is implicit rather than 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?

No annotations are present, so the description must carry the burden of behavioral disclosure. It indicates the feed contains published insights with trust scores and trending ranking, but does not explain default sorting (chronological vs trending), pagination, result limits, or whether trust scores are returned fields or filters. 'Browse' suggests read-only but that is not explicitly disclosed.

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?

A single sentence that front-loads the core action and resource, with no wasted words. It conveys the essential purpose efficiently and clearly.

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?

Adequate for a simple browse tool with all optional and documented parameters. However, with no annotations or output schema, it leaves default ordering, response shape, and the exact role of trust scores/trending ranking unspecified, which could lead to incorrect assumptions.

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 100%, with each parameter already explained (limit, agent_id, category, trending). The tool description adds no additional parameter-level meaning beyond what the schema provides, so the baseline 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?

Uses a specific verb 'Browse' and names a specific resource, the SoulLedger Stack feed, while adding content context (published insights from AI agents, trust scores, trending ranking). The purpose is clear, but it doesn't explicitly differentiate itself from sibling tools like soul_insights or soul_leaderboard.

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 guidance on when to use this tool versus alternatives. It implies using it to browse the feed, but there are no exclusions, prerequisites, or statements about choosing this over related tools such as soul_verify or soul_profile.

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 present, so the description carries the full burden of behavioral disclosure. It communicates that the operation is a verification and produces cryptographic proof, but it does not describe the response format, failure behavior, whether the operation is read-only, or any access requirements.

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 a clarifying em-dash clause. Every word contributes meaning, and there is no redundant or filler content.

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 one-parameter tool, the description covers the core action and purpose. However, with no annotations and no output schema, it omits the result shape, failure behavior, and explicit invocation context, leaving the agent to infer important call-time details.

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 100%, since the schema already explains agent_id as 'Agent identifier to verify'. The description adds context about hash-chain integrity but no additional parameter format, type, or usage specifics, 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 states a specific action ('Verify'), a precise resource ('agent's hash chain integrity'), and the intended result ('cryptographic proof of untampered history'). It is clearly distinct from the sibling soul_* tools, which target profile, insights, leaderboard, feed, and bounties.

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 the tool should be used when an agent needs proof that its history has not been tampered with, but it does not explicitly state when to prefer it over alternatives, any prerequisites, or when not to use 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?

With no annotations provided, the description carries the full burden of behavioral disclosure, and it explicitly states 'No side effects, no data changes — just structured thinking.' This clearly communicates the tool's non-mutating, safe nature, which is the only significant behavioral trait for a reasoning helper.

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 only two sentences long and front-loads the core purpose, immediately followed by the behavioral disclaimer and the 'Use when' list. Every sentence serves a distinct purpose with 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 simple one-parameter tool with no output schema and no annotations, the description fully covers the necessary context: what the tool does, that it has no side effects, and precisely when to use it. Nothing material is missing for an agent to select and 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 schema already provides full coverage (100%) for the only parameter, 'thought', describing it as the agent's reasoning, analysis, or plan. The description adds use-case context but no additional parameter-level meaning, 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 uses a specific verb phrase 'Pause and reason' and identifies the resource as 'a situation', then defines the tool as 'structured thinking'. It clearly distinguishes the tool from all sibling data-query tools by emphasizing that it performs no data fetching or side effects.

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 lists four concrete scenarios: processing tool results, verifying compliance rules, planning multi-step operations, and evaluating conflicting information. It does not explicitly name alternatives or state when not to use the tool, but the contrast with the query-focused sibling tools is obvious and the 'Use when' list provides strong guidance.

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 full burden. It discloses the key output contents and implies a current snapshot, but it does not mention data freshness, authentication needs, or explicitly confirm the operation is read-only with no side effects.

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 compact sentence that front-loads the resource and immediately lists the valuable outputs. Every phrase earns its place with 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 portfolio lookup, the description gives the essential content and is sufficient for correct invocation. Minor gaps remain around freshness/caching behavior and the exact format of layer allocations and P&L summary.

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 there is no parameter documentation burden. A baseline of 4 applies for a no-parameter tool.

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 (Wave Trader portfolio) and lists exactly what it provides: current holdings, total value, layer allocations, and P&L summary. This clearly distinguishes it from siblings like get_prices or wave_signal.

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 a read-only portfolio snapshot for Wave Trader, but it does not explicitly say when to use this tool versus alternatives such as get_prices or wave_signal. There is no stated exclusion or selection condition.

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 disclosure burden. It discloses that the output is a current, real-time signal with named fields, but it never explicitly states that calling it is non-mutating or that it does not execute trades; 'recommended action' could ambiguously suggest execution for a financial tool. This is a meaningful safety-related 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?

Two short sentences with no filler; the core definition and output fields are front-loaded, and the real-time framing is a single clause. This is appropriately sized for the tool's simple scope.

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 one-parameter tool with no output schema, naming the returned fields and token universe is mostly sufficient. However, the description omits output encoding, interpretation of the anomaly/confidence scores, and any safety caveats about the recommended action, leaving some ambiguity 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 input schema already documents the single token parameter at 100% coverage, so the baseline is 3. The description adds the Base L2 context and restates the OWB/MOLT enum values, which slightly reinforces meaning but does not add formatting, syntax, or additional 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 names a specific signal product and its output components (wave phase, anomaly score, confidence, recommended action) plus the token universe (OWB/MOLT on Base L2). It is clear enough to distinguish from generic pricing or query tools, though it is noun-led and does not explicitly contrast with prediction_signals or get_prices.

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 phrase 'Real-time market analysis' plus 'current wave phase' implies when the tool is relevant, but the description never states when to prefer it over sibling tools like prediction_signals or get_prices, nor when not to use it. Usage context is present but left to inference.

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