compliance-intelligence

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

The description explains important output behavior, including how baseline measurement versus reconstruction is reported and how non-comparable waves are handled. However, with no annotations, it does not explicitly disclose side effects or confirm that the tool is read-only, leaving some behavioral transparency burden unmet.

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 concise, well-structured, and front-loaded with the core purpose. It avoids unnecessary detail while still covering important output semantics and an edge case, making it easy to parse and understand.

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 description gives a solid overview of the returned summary content, including overall, process area, movement, baseline provenance, and comparability. It lacks explicit response format details and parameter guidance, but remains sufficiently complete for an agent to understand what the tool provides.

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 description mentions 'one engagement' but does not explicitly explain the engagement_id parameter, its source, or how to obtain valid values. Schema coverage is 0%, so the description adds little beyond the parameter name and type.

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 that the tool provides an adoption summary against baseline for one engagement, including overall, process area, and movement. It also explains key output distinctions such as baseline provenance and comparability, 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 does not provide any guidance on when to use this tool instead of sibling tools such as adoption_get_report or adoption_list_engagements. There is no mention of use cases, prerequisites, or alternative selection criteria.

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 partially carries the burden. It discloses that the output is a fact sheet with traceable evidence (responses/uploaded files) and clarifies it is not the rendered page. However, it does not mention side effects, permissions, rate limits, or error behavior beyond the 200 response.

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 relatively concise and well-structured, with a clear opening line, a brief elaboration on output, and a Responses section. It avoids excessive detail, though the phrase 'the latest management report as facts plus the evidence behind each one' is slightly redundant with 'Returns the fact sheet...'

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, the description covers the output well but omits any explanation of the parameter or how to obtain it. Without an output schema, the description of the evidence-carrying fact sheet is useful, but the missing parameter context leaves a gap in completeness.

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 coverage is 0% and the description provides no explanation of the required engagement_id parameter. The schema only gives type and minimum, leaving the agent to guess what an engagement_id refers to or how to obtain one.

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 retrieves the latest management report as a fact sheet with evidence, and explicitly distinguishes it from a rendered page. However, it does not explicitly contrast with sibling tools like adoption_get_adoption_summary, leaving some ambiguity about what a 'management report' uniquely covers.

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 the many sibling tools (e.g., adoption_list_engagements or agent_coverage_report). It does not mention conditions, prerequisites, or alternatives, so the agent must infer usage from the name alone.

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?

The description discloses the scope and that each engagement includes its current state, and 'List' implies a read-only operation. However, with no annotations, it does not mention whether the result is paginated, ordered, limited, or if there are any side effects or error conditions beyond the generic 200 response.

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 concise and front-loaded, with the core purpose in a single sentence. The included 'Responses' section is generic boilerplate but does not significantly bloat the description.

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, parameterless list operation, the description is largely complete: it identifies what is listed, whose engagements, and that current state is included. It does not specify response fields or ordering, but given the absence of an output schema and the simple nature of the operation, the description is 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 input schema has zero parameters, so there are no parameter descriptions needed. The description adds context by mentioning the signed-in consultant, which clarifies the implicit auth scope, but otherwise there is little parameter-specific meaning to add.

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 action ('List'), the resource ('adoption engagements'), and the scope ('the signed in consultant'), plus that each item includes its current state. It is specific enough, though it does not explicitly differentiate from related sibling tools like adoption_get_adoption_summary or adoption_get_report.

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 explicit conditions, exclusions, or alternatives. The description implies usage when a list of engagements is needed, but it does not state when not to use it or what distinguishes it from similar list/get tools.

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 does disclose the important traits: this is a real side-effecting mutation ('creates a real cart on the store'), it is free to call ('the course price is paid at checkout'), and it returns a checkout link. It omits auth/permission requirements, cart lifetime or abandonment, and idempotency, so it is not fully complete for a purchase 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?

Front-loaded and mostly waste-free: purpose, side effect, cost, prerequisite, and batching are each one sentence. The trailing '### Responses: **200** ... Content-Type: application/json' block is boilerplate noise that adds nothing for the agent.

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 usefully covers the return value (a checkout link). However, for a two-parameter purchasing tool it leaves the 'store' parameter and any error/permission behavior unaddressed, so an agent lacks full information to invoke it correctly in every 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?

Schema description coverage is 0%, so the description must compensate and only partially does. It clarifies product_ids is accept-one-or-more but never explains the wire format (the schema types it as a single string, so comma-separation is left to guesswork), and the 'store' parameter with default 'main' is not mentioned anywhere in the description or 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?

States a concrete verb and resource in plain terms ('Build a checkout for one or more courses', 'creates a real cart on the store and returns a checkout link'), and explicitly distinguishes itself from agent_search_courses, which only finds the product id. An agent can route between browsing and buying without opening either 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?

Gives an explicit precondition and sequencing ('Use agent_search_courses to find the product id first') and explains the multi-id case ('Multiple ids go in one cart... single transaction'). It does not state when NOT to use it (e.g., existing cart handling or preview/review alternatives), but context is otherwise unambiguous.

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 of behavioral disclosure. It clearly states that it returns a LINK and does NOT take payment, and that no card details pass through the agent. It also notes delivery timing for released vs. built-to-order pairs. However, it does not describe error responses or the exact structure of the returned link, leaving some gaps.

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 concise and front-loaded with the purpose. It uses two short paragraphs plus a minimal responses section, with every sentence adding valuable information: the action, delivery terms, payment behavior, and confirmation of the response type. No wasted 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?

Given the tool's simplicity (0 params, no output schema, no annotations), the description adequately covers the main aspects: what it returns, the payment process, and delivery. It could be more explicit about the exact format of the link or error handling, but for this simple tool the information is 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?

There are zero parameters, and the schema is empty with 100% coverage. Per the rubric, the baseline is 4 for 0 params. The description does not need to explain parameters and adds nothing about them, which is appropriate for a parameterless 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 clearly states the tool 'Get a checkout link for a crosswalk report' and explains it returns a payment link for a crosswalk between frameworks. This distinguishes it from sibling tools like agent_crosswalk_pair or agent_list_crosswalk_pairs, which are likely for generating or listing pairs, not buying them.

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 (when an agent needs to obtain a checkout link for a crosswalk) but does not explicitly state when to use this tool versus alternatives. It mentions 'Released pairs are delivered immediately' but offers no comparison to other tools or exclusions, so guidance is only implied.

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 full burden and excels: it discloses that it returns a link (not a payment), that no card details pass through the agent, that the buyer gets a single-use link upon payment, and that the output is draft language and a gap list—not a compliance certification. This goes far beyond a basic action statement.

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 well-organized: purpose, process, clarifications, and a response note. It's somewhat verbose but each sentence adds value. The '### Responses:' section is redundant and could be trimmed, but overall it's structured and 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?

Despite having no output schema, no annotations, and no parameters, the description fully covers the tool's behavior, what it returns, what happens after payment, and its limitations. It's self-sufficient and answers likely agent questions.

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 description doesn't need to explain any. It instead explains the purpose and flow. With 0 parameters, the baseline is 4, and the description adds no parameter-specific detail (unnecessary) but maintains clarity.

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 a clear, specific verb+resource: 'Get a checkout link for a single document compliance review.' This distinguishes it from siblings like crosswalk tools by focusing on a single document review. It also explains the outcome (link, not payment) unambiguously.

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 clearly states what the tool does and the context (buying a review against one framework). It notes it returns a link and does not take payment, which clarifies usage. However, it doesn't explicitly contrast with alternatives or state when not to use it, leaving some room for ambiguity among similar purchase tools.

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 disclose one notable behavior: concentration is reported when a single deal dominates a bucket, with a concrete illustrative example. However, it omits other useful behavioral traits such as time range, data granularity, or what the JSON response contains beyond a generic 200 note, so coverage is partial.

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 front-loaded with the core statement, then adds a useful distinction between sector and function, and a concrete example explaining the concentration behavior. The example is somewhat elaborate but earns its place by illustrating why concentration matters. It is concise enough for a human or agent to scan.

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 parameters, so input-side requirements are minimal, but there is no output schema and the description gives only a bare '200: Successful Response' line. It explains the conceptual classification and concentration caveat but does not specify what fields, aggregation, or format the JSON response will have. Acceptable for a report-style tool, but not fully 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?

The input schema has zero parameters, so there are no parameter semantics to clarify. The description's conceptual context is irrelevant to parameter meaning, and the zero-parameter baseline of 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 opens with 'Capital by the business function it targets' and elaborates 'Where the money went, classified by whose job it changes.' This clearly identifies the resource (capital) and the classification dimension (business function), and distinguishes function labels from sector labels. It lacks an explicit verb like 'list' or 'report,' but the intent is 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 explains why function-based classification is actionable and explains concentration reporting, but it never tells an agent when to pick this tool over any of the many siblings. There is no 'use this when' or 'instead of X' guidance, leaving the selection entirely to inference from the name and subject matter.

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, so the description bears the full burden. It does disclose cost ($0.015 per call via x402 USDC on Base, free with a Professional API key) and roughly what the response contains (union coverage, marginal gains, unreached areas), but says nothing about auth requirements beyond the key, rate limits, or error behavior.

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 purpose is front-loaded, but pricing/marketing copy ('the marginal number is the one worth knowing', the parenthetical about certification marginality) consumes space that would be better spent on input and output format. Every sentence is readable but not all of them earn their 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?

No output schema and no annotations, so the description must carry return-value and behavior detail. It gives one sentence on the response shape and covers pricing, but omits the string format of both inputs and any detail on how 'coverage' is represented, leaving an agent to guess at invocation specifics.

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% for both required parameters. The description maps the semantic roles ('frameworks an organisation already holds' and 'one it needs') onto holds/target, but with plural frameworks encoded as a single string it leaves the format (comma-separated names? IDs? codes?) entirely unspecified, so it only partially compensates for the coverage gap.

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?

States a specific computation: given the frameworks an organisation holds and the one it needs, it returns combined coverage, marginal additions, and gaps. The verb+resource is clear and it is distinguishable from sibling crosswalk/coverage tools, though it never names a sibling to differentiate against.

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?

Names two free alternatives (agent_crosswalk_pairs, agent_search_frameworks) and the condition (no payment or key), and explains the motivating scenario ('No organisation holds one certification'). There is still no guidance on when to prefer agent_coverage_report or agent_crosswalk_pair over this tool.

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 provide meaningful behavioral detail: matching is against requirement text, not title; it intentionally returns nothing rather than strained matches. This is substantive non-obvious behavior. However, it stops short of describing permissions, output shape, or other operational traits.

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 fairly tight and front-loads the main idea. The 'The join.' fragment and the somewhat aphoristic warning about title matches add flavor but not much structural value; still, most sentences earn their 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?

There is no output schema and no annotations, yet the description only says a successful response is JSON and that the tool may return nothing. It does not describe the actual result shape, ordering, pagination, or how limit and min_hits shape the response, leaving a real gap for an agent trying to use the result.

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 75%, so the schema already explains capability, min_hits, and framework. The description adds context that capability means 'funded capability' and that matching targets the control's requirement text, but it adds no detail about limit, min_hits behavior, or framework restriction beyond what the schema provides.

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 relation—controls that a funded capability actually touches—and clarifies the core matching mechanism (requirement text, not title). It is not a tautology and conveys enough to distinguish the tool from generic crosswalk/search siblings, though the phrase 'The join' is somewhat cryptic.

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: when you have a capability and need the controls whose text genuinely concerns it. It does not state explicit when-not-to-use conditions or mention alternative sibling tools, so the guidance is mostly implicit rather than directive.

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 real behavioral context: the call is FREE, needs no API key, and requires no payment, and the response includes a `buy_url`. It still says nothing about error behavior for an invalid `product_id` or about how large courses are returned, so it is good but not exhaustive.

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 value proposition is front-loaded in the first line, followed by cost/auth facts and usage guidance in a tight block. The trailing 'Responses: 200' block is boilerplate padding rather than useful content, a minor deduction.

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 single-parameter tool with no output schema and no annotations, the description covers what the tool returns (modules, chapters, summaries, buy_url), when to use it, and its cost/auth profile. The only real gap is the absence of any sibling comparison against `agent_get_course`.

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%, so the description must compensate, and it does by explaining where `product_id` comes from (agent_search_course_content or agent_search_courses), which is actionable guidance beyond an undocumented integer field. It omits the expected format/type, keeping it out of 5 territory.

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 and scope: 'the full teaching structure of one course: every module with its summary and every chapter inside it.' That is far more than a restatement of the name. It does not, however, distinguish itself from the similarly-named sibling `agent_get_course`, leaving a potential ambiguity unaddressed.

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 gives an explicit use case ('confirm a course genuinely covers a requirement before recommending it to someone') and tells the agent where to source the required `product_id` (agent_search_course_content or agent_search_courses). It does not name an alternative tool for when the lighter-weight `agent_get_course` would suffice, so it falls short of the 5 benchmark.

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 clearly states that no authentication is required, which is a helpful behavioral note. It also explains fallback behavior when no single course spans all standards. However, it does not disclose potential side effects or rate limits. For a read-only search tool, this is adequate, and a 4 is justified given the added context 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?

The description is four sentences long, efficient and front-loaded with the core purpose. The example is helpful but could be integrated more tightly. Every sentence adds value, though the response section adds minimal new information beyond the schema. Still, it is well-structured and concise.

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 two parameters, no output schema, and no annotations, the description covers the essential: what the tool does, how to use it (with example), fallback behavior, and authentication context. It could mention return format more explicitly, but the response 200 hint in the description partially covers that. The tool is relatively simple, so completeness is high.

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 50%, meaning one parameter (frameworks) has a description in the schema. The description compensates by providing an example ('SOC 2,ISO 27001') and explaining the semantics of the frameworks parameter. The limit parameter's default and constraints are already in the schema, so the description adds minimal extra meaning. Overall, the description adds value 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 uses a specific verb phrase 'Find courses covering several standards at once' and clearly identifies the resource (courses covering multiple frameworks). It distinguishes itself from sibling tools like agent_search_courses by emphasizing multi-standard coverage for organizations running overlapping programs.

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 when to use the tool ('when an organisation running overlapping programmes actually needs' courses addressing ALL standards together) and provides a clear example (frameworks='SOC 2,ISO 27001'). It also explains fallback behavior ('returns courses on running both from one evidence set, rather than one course per standard') and notes that no authentication is required. No explicit exclusion of alternatives, but the context and example guide usage well.

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 does so well: it discloses the cost ($0.015 per call via x402/USDC on Base), the exact failure behavior of an unpaid call (402 with a PAYMENT-REQUIRED challenge carrying amount, asset and address), the free-key path, and the guarantees on the data (derived judgements that survived adversarial verification). It also pre-empts a likely misread by stating that an absent mapping is reported explicitly rather than as zero coverage.

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 critical information (what it returns, example, derivation caveat, pricing) is front-loaded, and the alternative/free routing is appropriately placed last. The opening fragment and the dense payment clause add some reader burden, but nearly 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?

There is no output schema, and the description does describe the shape of the result (covered controls, gaps, per-claim reasoning, and the no-mapping case). Payment mechanics and free alternatives are covered, which is unusually complete. It is only marginally short on how the response is structured or paginated, which prevents a 5.

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 source, target and min_confidence with examples. The description repeats the source/target framing and adds nothing about the semantics of min_confidence (what high/medium/low actually filter). Baseline 3 is appropriate when the schema does 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 states a specific computation: given a held framework and a target framework, it returns which of the target's controls are already evidenced, which are gaps, and the reasoning behind each claim. It is far more than a restatement of the name and includes a concrete example pair. It names some siblings as free alternatives but does not distinguish itself from close siblings like agent_cross_framework_map or agent_combined_coverage, which keeps it off a 5.

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 clearly frames the use case ('a framework you already hold and one you are working toward') and routes users of the free-tier catalogue to agent_crosswalk_pairs, agent_search_frameworks and agent_get_framework. However, it does not say when to prefer this over the many other crosswalk/mapping siblings (agent_cross_framework_map, agent_crosswalk_pair, agent_combined_coverage), so no explicit exclusions are given.

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 exist, so the description carries the full burden, and it does meaningfully disclose the payment model ($0.015 per call over x402 in USDC on Base, or free with a Professional API key) plus the free no-payment options. It also describes the return shape. It omits error/failure behavior and any rate limits, keeping it short of a 5.

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?

Front-loads the purpose, then payment details, then return contents and use case. Dense but every sentence contributes; only minor redundancy between the 'coverage analysis' phrasing and the following enumeration.

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 and no annotations, the description covers purpose, return content, payment model, and use case adequately. The main residual gap is parameter format detail, which is left ambiguous.

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% for the single 'name' parameter, so the description must compensate. 'For a framework' implies the parameter is a framework identifier, which adds some meaning, but it never clarifies whether the value is a slug, ID, or display name.

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?

States a specific verb and resource: get a cross-framework coverage report for a framework, and specifies the return content (total controls, mapped counts, coverage percentages per target framework). It does not differentiate itself from close siblings like agent_coverage_crosswalk, agent_combined_coverage, or agent_cross_framework_map, leaving the agent to infer which coverage tool is which.

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 an implied use case (understand which frameworks overlap and plan multi-framework strategies) and notes free alternatives, but those named tools (agent_crosswalk_pairs, agent_search_frameworks) are free substitutes rather than the same-purpose alternative. No explicit when-to-use vs. when-not guidance relative to the overlapping coverage siblings.

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 does substantial work: it discloses per-call pricing ($0.015 via x402 USDC on Base), that a Professional API key is served free, which tools are free without payment, and the shape of the return (complete control-to-control mapping). It still omits error behavior and any rate/limit details, but the cost/auth disclosure is genuinely valuable.

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?

Purpose and pricing are front-loaded and each block earns its place, though 'Returns the complete control-to-control mapping...' and 'Each mapping shows which source control maps to which target control(s)' restate the same idea and could be merged.

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 two-parameter tool with no output schema and no annotations, the description covers purpose, cost, alternatives, and return semantics adequately. It leaves out failure modes for invalid framework names, which is a minor 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?

Schema coverage is 100%, so the baseline is 3, but the description adds actionable meaning: 'Use exact framework names as returned by agent_search_frameworks,' which tells the agent how to obtain valid values beyond the schema's static examples.

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?

States a specific verb+resource: 'Map controls between two compliance frameworks,' and clarifies the direction (source to target). It further distinguishes itself by naming the free siblings agent_crosswalk_pairs and agent_search_frameworks, so an agent can tell when this paid tool is the right pick.

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?

Gives a clear use context: multi-framework compliance (satisfy one control to cover both frameworks) and, importantly, names free alternatives for the same need. It stops short of explicitly contrasting with the similar-looking sibling agent_crosswalk_pair, so the routing guidance is not fully exhaustive.

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 does well on the highest-stakes trait: cost ($0.015 USDC on Base), the 402 PAYMENT-REQUIRED challenge shape (amount, asset, address), and the free-with-API-key path. It is silent on what happens for a non-existent pair, rate limits, and the default sample size of 8, which is a meaningful omission for an unannotated paid endpoint.

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?

Good front-loading with the payload description first and the payment/routing information last, but the middle paragraph contains rhetorical filler ('a number nobody argued with', 'not an appendix') that informs a human reader more than an agent. The payment paragraph, by contrast, earns every sentence.

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 no annotations, so the description must do more work than it does. It describes the conceptual return content well, but leaves the two required identifiers' format, error behavior for unknown pairs, and the default sample size unexplained, which are exactly the details an agent needs to invoke this 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 0% and all three parameters (source, target, limit) are undocumented. The description never says whether source/target take framework IDs, slugs, or names, nor does it name or bound the limit parameter beyond loosely implying that samples are returned. Only a faint hint about sampling partly compensates for the coverage gap.

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 the exact resource and scope: one crosswalk pair in full, explicitly including rejected claims. It then enumerates the payload (coverage percentage, sample of held claims with reasoning, sample of refuted claims with failure reasons) and differentiates itself from the free list/search/get siblings. An agent can tell what this returns without opening the 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 selection context clearly for the paid/free split: without payment the call returns 402, a Professional API key is served free, and it names three free alternatives (pair listing and framework catalogue lookups). What it does not do is contrast itself with the closely related siblings agent_crosswalk_refuted and agent_crosswalk_provenance, which overlap in subject matter.

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 does disclose useful behavioral context: it is a paid read at $0.015/call over x402 with a free Professional API key alternative, and it describes the return content (provenance, verification dates, adversarial survival). It does not state error behavior for unknown pairs, rate limits, or response format beyond the 200 status.

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?

Purpose is reasonably front-loaded, but the rhetorical opening ('How do you know this...') and the closing flourish ('A claim you cannot check is worth nothing...') consume space without adding invocation guidance. The pricing sentence earns its place; the aphorism does not.

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 no annotations, so the description must carry the return-value explanation, which it does well by enumerating what provenance fields are returned. However, parameter semantics for source/target/limit are left thin, so the definition is only adequately complete for a 3-parameter 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?

Schema description coverage is 0% for all 3 parameters. The phrase 'any released framework pair' implies source and target are frameworks, but no format or valid value guidance is given, and the `limit` parameter (default 25) is never mentioned in the description.

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 and resource ('return the reasoning and the provenance behind its mappings') and enumerates the exact artifacts returned (verification document, date, judge, adversarial pass). It is clearly distinct from siblings like agent_crosswalk_pair or agent_crosswalk_refuted, though it doesn't name those siblings explicitly.

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?

'For any released framework pair' sets the context for invocation, implying it operates on existing crosswalk pairs. However, it gives no explicit when-to-use guidance relative to the other crosswalk tools (agent_crosswalk_pair, agent_crosswalk_refuted) and no statement about what happens for unreleased pairs.

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 the full behavioral burden. It usefully discloses cost/auth ('$0.015 over x402... Professional API key served free') and a real behavioral trait ('Refuted mappings are kept in the graph rather than deleted'), but omits return shape, pagination, and any error or auth-failure behavior.

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?

Reasonably sized, but the billing sentence is inserted mid-paragraph and interrupts the flow between the concept and the 'refuted mappings are kept' rationale. The core purpose is front-loaded, but the pricing aside crowds the structure.

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 three params at 0% schema coverage and no output schema, so the description should do more to explain inputs and results. It explains the concept and data-retention behavior well, but leaves the parameters and the returned structure undocumented.

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% for three parameters. The phrase 'for a pair' vaguely gestures at source/target, but their expected format (framework identifiers vs names) is never stated, and the 'limit' parameter is not mentioned at all in the description.

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 resource: 'The mappings that were proposed for a pair and then refuted, each with why it failed', which is a specific verb+resource distinct from siblings like agent_crosswalk_pair and agent_crosswalk_provenance. The poetic opener 'What was claimed and did not hold' is less precise but the following sentence resolves it.

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 offers implicit guidance ('This is the check worth running on any coverage claim') and names free alternatives for cost reasons, but does not say when to choose this over the closely related agent_crosswalk_pair or agent_crosswalk_provenance siblings, nor what conditions select 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. It only mentions a successful 200 response and fails to address error conditions (e.g., invalid code), authentication requirements, rate limits, or any side effects. The description is insufficient for an agent to fully anticipate the tool's behavior.

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 concise, using a clear title line and a short paragraph. The inclusion of a 'Responses' section adds structure, though it is minimal (only 200). Overall, every sentence contributes value without unnecessary verbosity.

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 has one parameter, no output schema, and no annotations, the description covers the basic purpose and return fields. However, it omits error handling, response format details beyond 'Content-Type: application/json', and any prerequisites. For a simple retrieval tool, this is adequate but not fully comprehensive.

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 has 0% description coverage, so the description must compensate. It explains the 'code' parameter as a framework-specific identifier with examples ('A.5.1', 'AC-1'), which adds meaning beyond the bare schema. However, it does not specify valid formats, patterns, or how to obtain valid codes, leaving some ambiguity.

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 retrieves detailed information for a single control by its code identifier, listing the fields returned (title, description, domain, framework) and providing examples of framework-specific codes. While it distinguishes from sibling tools like agent_get_framework_controls (which lists multiple controls) by emphasizing a single control lookup, it does not explicitly delineate from all 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?

The description lacks any guidance on when to use this tool versus alternatives such as agent_get_framework_controls or agent_search. It does not specify prerequisites, when not to use it, or any context-dependent recommendations, leaving the agent to infer usage from the tool name alone.

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 must fully disclose behavioral traits. It describes the relationship type (MAPS_TO) and gives an example, but lacks information on pagination, potential large response size, error conditions (e.g., control not found), and whether the operation is read-only. The basic function is conveyed, but important behavioral details are missing.

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 description is two sentences and an example, which is concise. However, the 'Responses' section is poorly formatted and adds noise ('200: Successful Response (Success Response)') without providing useful information. This detracts from the overall conciseness.

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 is simple (one parameter, no output schema), and the description explains the mapping concept and use case. However, it lacks explicit parameter documentation, behavioral details (pagination, errors), and does not leverage the sibling list to differentiate. 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?

Schema description coverage is 0%, so the description must compensate. It implies that 'code' is the identifier of the control (e.g., from the example 'AC-1'), but it does not explicitly define the parameter's format, expected values, or provide an example. The description adds some meaning beyond the schema but is not fully explicit.

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 'Get cross-framework mappings for a control' and explains it returns controls mapped via MAPS_TO relationships. However, it does not differentiate from the sibling tool 'agent_cross_framework_map', which likely has a similar purpose. The example (NIST 800-53 equivalents of ISO 27001) adds concreteness.

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 says 'use it to find equivalent controls across different compliance frameworks' which implies the context of use. However, it does not specify when not to use it or mention alternatives, particularly the sibling 'agent_cross_framework_map'. The usage context is implied but not 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?

With no annotations, the description must cover behavioral traits. It discloses the response includes specific fields, the HTTP status (200), and that no auth is needed. However, it omits potential error conditions, rate limits, or data freshness policies, which are relevant for a read 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?

The description is short but includes minor redundancy (e.g., 'Get one course' echoes the name) and a blank line. The 'Responses' section adds minimal value. It front-loads the purpose effectively but wastes some space.

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 single-parameter tool with no output schema, the description covers the core functionality, parameter usage, ordering relative to search, and response content. Missing error handling details, but overall it is sufficient for an agent to use 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?

The only parameter (product_id) has no schema description, so the description must add meaning. It does say 'by product id' linking the parameter to the resource, but fails to explain what constitutes a valid ID, where to find it, or any constraints beyond being an integer.

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 explicitly states the tool retrieves a single course by product ID, listing included details (standards, purchase URL). This clearly distinguishes it from sibling tools like agent_get_control or agent_get_framework.

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 advises using this tool after agent_search_courses to justify a recommendation, providing explicit context. It also notes no authentication required. However, it does not list when to avoid the tool or name specific alternatives beyond the suggested sequence.

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 must carry full behavioral disclosure. It implies a read-only operation via 'Get' and lists the return fields. However, it does not explicitly confirm safety, mention authentication requirements, rate limits, or error behavior. This is adequate for a simple retrieval tool but lacks comprehensive transparency.

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 concise—one sentence for purpose, one for guidance, and a brief response note. It is front-loaded with the core verb and resource. Minor waste: the response section only mentions a 200 status without expanding on format, but this keeps it lean. Overall well-structured for its length.

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 (one required parameter, no output schema, no nested objects), the description covers the return content sufficiently—listing the key fields (description, jurisdiction, version, domains, mapping stats). It does not address error cases or edge conditions, but for a get-by-name tool this is reasonably 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?

The input schema only defines a required 'name' string with no description (0% schema coverage). The description adds significant meaning: 'Use the exact framework name as returned by agent_search_frameworks.' This tells the agent where to source the value and emphasizes exactness, going well beyond the raw 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 explicitly states 'Get detailed information about a compliance framework' and lists specific attributes (description, jurisdiction, version, domains with control counts, cross-framework mapping statistics). This clearly distinguishes it from sibling tools like agent_get_framework_controls and agent_search_frameworks.

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 a direct usage hint: 'Use the exact framework name as returned by agent_search_frameworks.' This tells the agent how to obtain the correct parameter value. However, it does not explicitly compare when to use this tool versus alternative siblings like agent_get_framework_controls, leaving a minor gap.

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 structure of the response (each control includes code, title, description, domain), which is helpful. However, it does not mention any side effects, rate limits, or authorization requirements, leaving moderate gaps.

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 concise (two well-structured sentences plus a list) and front-loads the purpose and key usage advice. Every sentence adds value without 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?

Given the tool's moderate complexity (2 parameters, one required, no output schema), the description adequately covers the purpose, usage hints, and response structure. It would benefit from mentioning whether the response is paginated or truncated for large frameworks, but it is largely complete for its scope.

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%: the description does not explain the 'name' parameter beyond the schema's requirement, but it does describe the result structure. The 'domain' parameter is already described in the schema ('Filter controls by domain name'), so the description adds little beyond that. Baseline 3 is appropriate given moderate 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 uses a specific verb-resource pair ('Get all controls for a compliance framework') and clarifies the scope by mentioning optional domain filtering. It also distinguishes this from sibling tools like agent_get_control (single control) and agent_search_frameworks (search, not retrieval).

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 advises using the domain filter for large frameworks (e.g., NIST SP 800-53 Rev 5), which helps an agent decide when and how to invoke the tool effectively. However, it does not explicitly state when NOT to use it or mention alternatives among siblings.

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 of behavioral disclosure. It discloses that the tool is 'Free, no authentication' and explains the routing behavior that makes it succeed where the sibling fails. However, it does not describe the response format beyond a brief '200: Successful Response', nor does it mention any potential pagination or limit on controls returned. Still, the important behavioral detail (the URL routing issue) is well explained.

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 moderately concise, with a clear front-loaded definition of the tool's purpose. It includes a substantial explanatory section about the routing issue that is relevant but slightly verbose. Overall, it is well-structured and each sentence contributes to understanding the tool's purpose and usage.

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 that the tool is a simple get operation with a small input schema and no output schema, the description is fairly complete. It explains the key nuance about forward slashes, authentication, and parameter placement. The only minor gap is the lack of detail about the response shape, but since there is no output schema and the tool's purpose is clear, the description is adequate.

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 has 100% coverage with parameter descriptions, including an example for 'name' ('CCPA/CPRA') and a filter description for 'domain'. The tool description reinforces the key parameter semantics by explaining that 'name' is a query parameter and adding the context that it must be the exact framework name. While the description doesn't add more detail on 'domain', the schema already covers it, so the marginal value is decent but not maximal.

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 purpose: 'Get all controls for a framework, naming it as a query parameter'. It identifies the principal action (get controls) and the resource (framework) via a query parameter. It also explicitly distinguishes this tool from its sibling 'agent_get_framework_controls' by noting the different parameter placement and use case (for frameworks with forward slashes).

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 guidance on when to use this tool: 'Use this whenever the framework name contains a forward slash'. It also explains why the alternative path-based route fails (server decodes %2F, causing 404), and clarifies that this route 'works for every framework'. This provides clear when-to-use and when-not-to-use 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 provided, the description carries full burden. It discloses 'No authentication required' and implies read-only behavior. However, it omits details like pagination, error responses, or whether data is live vs cached. More behavioral context would be helpful.

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 information is front-loaded in two sentences plus a brief authentication note. The 'Responses' section is slightly redundant but does not detract. It is concise without being under-specified.

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 parameterless listing tool, the description is largely sufficient. However, given the absence of an output schema, it could be more complete by describing the exact response fields beyond just 'course count'. The structure of the returned objects is not fully clarified.

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 no parameters, and schema description coverage is trivially 100%. According to rubric, zero parameters earn a baseline of 4. The description does not need to add parameter meaning, and it correctly focuses on purpose instead.

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 explicitly states 'List standards the catalogue covers' and clarifies it returns each standard with a course count. It distinguishes the tool as a discovery mechanism for framework filter values, which differentiates it from sibling search/retrieval tools like agent_search_frameworks or agent_get_framework.

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 directly says 'Use this to discover valid values for the framework filter before searching.' This gives clear when-to-use guidance. It does not explicitly exclude alternatives, but the positive usage context is strong and sufficient given the sibling tools.

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 transparency burden. It discloses that no authentication is required, and that unreviewed pairs return an honest 'not released' rather than a percentage. It does not describe response format details, but the 200 response section hints at JSON. This is reasonable for a simple list 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?

The description is concise and well-structured: a clear opening, usage context, behavior note, authentication statement, and response hint. The sentence about building pairs to order adds some extra context but is not excessive. It 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?

For a zero-parameter list tool with no output schema, the description covers purpose, usage, behavior for missing pairs, and authentication. The only gap is a precise JSON response format, but the 'Responses' section and phrase 'coverage figure for each' give enough for a simple list. It is adequate and complete for the tool's complexity.

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 adds no parameter details (none needed) but does clarify the output includes a coverage figure per pair, which is relevant context though not about inputs.

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?

Purpose is explicit: lists framework pairs with a reviewed, signed-off coverage crosswalk and the coverage figure for each. Clearly distinguishes from sibling tools by its focus on released crosswalks and the coverage value, and it names the associated tool agent_coverage_crosswalk.

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 instructs to call this before agent_coverage_crosswalk to identify which pairs return a number. Also states that pairs not listed are unreviewed and will return 'not released', giving clear when-to-use and exclusion 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?

The description notes no authentication required, which is useful for behavioral expectations. However, with no annotations provided, there is no contradiction, but the description could add more detail about rate limits, data freshness, or whether the counts are cached. The current info is adequate but 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 extremely concise with two short sentences, no filler, and all information is front-loaded. Every sentence is necessary and to the point.

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 this is a simple, parameterless stats tool with no output schema, the description provides sufficient detail about what statistics are returned. It does not include potential response structure or edge cases, but for such a straightforward tool, it is complete enough.

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% (no parameters to document). The description adds value by specifying the exact data returned (total framework count, control count, etc.), which goes beyond the bare 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 clearly states it returns platform statistics and specifies the exact counts provided (framework count, control count, cross-framework mapping count, domain count). This distinguishes it from sibling tools that focus on specific frameworks, controls, or courses.

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 states that no authentication is required, implying it's a low-risk, generally useful endpoint. It does not explicitly mention when to use it vs alternatives, but the purpose is clear enough to infer it's for a broad overview, while siblings are for specific resources.

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 full burden. It correctly indicates a read operation (returns data, no side effects) and notes conditional behavior based on authentication. However, it does not describe exactly what happens when unauthenticated or disclose other behavioral traits like latency or rate limits. It is adequate but lacks full transparency.

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 concise with two sentences and a response code header. It is front-loaded with the purpose and return content. The 'Responses' section adds minimal value but does not bloat the text. Every sentence serves a purpose, making it appropriately sized.

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 no output schema and zero parameters, the description explains what the tool returns and when to use it. However, it does not detail the structure of pricing tiers or call limits in the response, leaving the agent to infer the format. While sufficient for basic usage, a more complete description would outline the JSON fields returned.

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 schema coverage is trivially 100%. Per guidelines, the baseline is 4. The description does not need to add parameter details, and it does not attempt to, so a score of 4 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 clearly states the verb 'Get' and the resource 'API pricing and rate limit information', specifying the returned data including pricing tiers, call limits, and optionally current usage. It distinguishes itself from all sibling tools, which focus on courses, frameworks, and controls.

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 states 'Use this to understand costs before making API calls', which provides clear context for when to invoke the tool. It does not explicitly exclude scenarios or name alternatives, but given no sibling tool with overlapping purpose, this is acceptable and 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?

With no annotations provided, the description carries the full burden. It describes the search behavior adequately but does not explicitly state that it is a read-only operation or disclose any side effects. Given the straightforward search functionality, the description is minimally sufficient but lacks explicit safety or behavioral guarantees.

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 front-loaded with the core purpose but includes an unnecessary 'Responses' section that merely states a 200 HTTP status code. This adds noise and reduces conciseness. The main body is clear but could be tightened.

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 description covers the search functionality and parameter usage reasonably well, but it lacks any details about the return format or structure of results. Given no output schema, the agent is left without expectations for what the tool returns. This is a notable gap for a search 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?

Schema description coverage is 100%, so the description adds little beyond what the schema already provides. It repeats examples from the schema and gives a usage tip, but does not deepen understanding of parameter semantics or add new constraints. 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 clearly states it performs full-text search across controls and frameworks, and distinguishes between the two types via the 'type' parameter. However, it does not explicitly differentiate from sibling tools like 'agent_search_frameworks' or 'agent_search_courses', which could cause confusion about which tool to use for framework search.

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 a usage tip ('use specific compliance terms for best results') but offers no guidance on when to use this tool versus alternatives like 'agent_search_courses' or 'agent_search_frameworks'. There is no explicit when/when-not advice or comparison with siblings.

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 disclosure burden, and it delivers real context: FREE, no API key, no payment, plus what a response contains (matching courses, the specific chapter, and a buy_url). It does not cover pagination or rate/limit behaviour, so it stops just short of full transparency.

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?

Front-loads the core purpose ('Search what courses teach') and the key routing contrast, then adds supporting detail. Slightly dense with formatting and stats (126,803 courses), but each sentence adds selection value rather than repeating structured fields.

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 returns, and it does: courses that teach the capability, the chapter, and a buy_url. Combined with the cost/auth disclosure it is nearly complete for a 2-param search tool; only limit/pagination behaviour is unspecified.

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%, so the description must compensate. It does for the critical 'q' parameter: examples ('evidence for access reviews', 'segregation of duties in SAP') and the guidance to query a CAPABILITY rather than a product name materially change how an agent constructs the query. The 'limit' parameter is left unexplained, keeping it out of the top score.

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?

States a specific verb and resource — full-text search over the teaching content (module titles, summaries, chapter titles) of 126,803 courses. It explicitly distinguishes itself from the sibling agent_search_courses by scope (content vs product names), so an agent can pick the right tool without opening either 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?

Gives an explicit usage rule: 'Use this when someone asks how to do something rather than what to buy.' It also names the alternative (agent_search_courses) and the condition that selects it. Nothing is left 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 full burden. It discloses key behavioral traits: returns up to 25 courses, includes a direct purchase URL, and requires no authentication. It does not cover rate limits, error handling, or pagination, but the information given is sufficient for a read-only search 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 efficiently structured: a one-line summary, then context, examples, result details, and authentication status. Every sentence contributes useful information, and 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?

The description covers core functionality, parameters, and result limit, but lacks detail on the return format (beyond 'URL') and does not mention error responses. Given the absence of an output schema, the description should have elaborated on the course fields returned to achieve full completeness.

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 67% (q and framework described, limit not). The description adds significant value by providing concrete examples for q ('soc 2 evidence collection') and framework ('ISO 27001'), and clarifies the limit parameter's maximum via 'Returns up to 25 courses'. This compensates for the missing schema description on limit.

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 searches the course catalogue via free-text, optionally narrowed by framework. The verb 'search' and resource 'course catalogue' are specific, and the option to narrow by framework distinguishes it from siblings like agent_get_course (specific course) and agent_search (general search).

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 context for when to use the tool (searching courses by need, framework, role, or industry) but does not explicitly contrast it with siblings such as agent_courses_for_frameworks or agent_search. The usage is implied but lacks clear when-not-to-use or alternative 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 provided, the description carries the burden of disclosing behavior. It explains the return fields and the no-query behavior, which is useful. However, it does not address potential side effects, read-only guarantees, sorting, or error scenarios—though these are less critical for a search 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 concise and front-loaded with the core purpose. The 'Responses' section is somewhat redundant, but it is small and does not detract much. Overall, it is efficient and well-organized.

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 read-style search tool with four well-documented parameters and a clear return description, the details provided are largely complete. The absence of an output schema is mitigated by the explicit list of returned metadata fields, but more detail about result ordering or filtering edge cases could add value.

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 schema itself provides detailed parameter descriptions including examples and pagination semantics. The description adds slight context by mentioning search dimensions (name, keyword, jurisdiction) and the no-query case, but it does not substantially go 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 clearly identifies the action ('Search and list compliance frameworks'), the resource ('compliance knowledge graph'), and the result (framework metadata). It also differentiates itself from sibling tools by presenting itself as the starting point for framework discovery.

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 states 'Use this as the starting point to discover available frameworks,' providing clear context for when to invoke it. It also explains the behavior when no query is supplied. It does not explicitly name alternatives or exclusion scenarios, but the guidance is sufficient.

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 must carry the behavioral burden. It discloses only that a 200 response is successful and returns JSON, but says nothing about side effects, read-only status, pagination, limits, or error behavior. This is effectively no meaningful behavioral guidance.

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 short but not effective; it consists of cryptic promotional phrases rather than clear, instructive content. It is under-specified rather than concisely informative, and the opening line adds no operational value for an AI agent deciding to call the tool.

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 three parameters, no output schema, no annotations, and a large sibling set, the description is severely incomplete. It does not explain what the tool returns, how to use the parameters, what the response represents, or when this tool is appropriate. An agent would have almost no basis for correct 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?

The description mentions 'a framework, a function, and the controls,' which loosely echoes the framework and function parameters, but it adds no concrete meaning beyond the schema. The schema already documents framework and function; limit remains undocumented by the description. With schema coverage at only 67%, the description should compensate but does not.

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 is vague and poetic ('Where a framework meets where the money is going') rather than stating a clear verb and resource. It never explicitly says what the tool does, such as retrieving, calculating, or exposing something. It does not distinguish itself from the many sibling tools or the name 'agent_signal_exposure'.

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 explicit guidance on when to use this tool versus any alternative. The text refers to a 'brief' and 'money is moving into this capability,' but does not state conditions for use, exclusions, or preferred scenarios. A reader is left to infer the intended use.

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 burden and does well: it enumerates exclusions (rate decisions, price targets, bond issues, etc.) and states that a rejected count is returned alongside the rows. This gives the agent useful insight beyond a simple list 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?

The description is front-loaded with the core purpose and uses a clear structure with a short paragraph and bullet-style list of exclusions. The 'Responses' section is somewhat redundant but not bloated enough to hurt readability.

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 filtering behavior and the returned rejected count are well covered, and the parameters are mostly self-explanatory from the schema. However, the exact meaning of 'current window' is undefined, there is no output schema, and no details about pagination or response structure beyond a 200 JSON response.

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 describes three of the four parameters with meaningful text, and the description adds little parameter-level detail beyond that. The undocumented 'limit' parameter is still understandable from its name, type, and min/max constraints.

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 returns genuine funded rounds in the current window with their sources. It uses a specific noun phrase and scope, but does not explicitly distinguish itself from sibling tools like agent_signal_exposure.

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 use when funded-round signals for the current window are needed and notes what is already filtered out. However, it provides no explicit when-to-use vs when-not-to-use guidance or references to alternative sibling tools.

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