Decision Anchor

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

No annotations provided, so the description carries the burden. It mentions the tool costs DAC and returns anomaly results, but does not disclose whether it is destructive, authentication requirements beyond the auth_token parameter, or rate limits. The payment flow is partially described in the schema but not elaborated in the description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: the first states the action, the second summarizes the output. No redundant words. Front-loaded with key information.

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, the description at least names the 5 dimensions. However, it does not specify the response structure or how to interpret the results. With 4 parameters well-described in schema, it is mostly complete but could benefit from more output details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description does not add semantic value beyond the schema. It mentions output dimensions but no additional parameter context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool compares a decision against an accumulated pattern and returns band_position for 5 specified dimensions. It also mentions it costs DAC, which is distinctive. It is distinct from siblings like 'get_environment_anomaly' and 'observe_pattern'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. The description does not state when not to use or mention alternative tools like 'get_environment_anomaly' or 'observe_pattern'. Usage context is implied but not clarified.

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?

Without annotations, the description carries the burden of behavioral disclosure. It adds context about the external record settlement, the timing of the integrity hash/timestamp (created at declaration time), and that confirm requires only dd_id. However, it doesn't disclose reversibility, idempotency, or error behaviors—leaving gaps for a mutating 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 five sentences, but there is redundancy: 'Confirm a pending decision — marks the anchored declaration as settled' restates the first sentence's purpose, and 'Call this after the action described in the DD has been executed' repeats the 'Use after create_decision' cue. Some trimming could improve 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?

For a simple tool with two fully described parameters and no output schema, the description provides sufficient context: it explains the placement in the workflow (after create_decision and after execution), the external record effect, and the dd_id requirement. It lacks return-value details, but the action is straightforward enough that this isn't a critical 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% for both parameters, so the baseline is 3. The description adds value by clarifying that 'confirm requires only the dd_id' and that the integrity hash/timestamp are from create_decision, not confirm. This enriches the meaning of dd_id beyond the schema's simple 'The DD ID to confirm'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Confirm a pending decision — marks the anchored declaration as settled.' It uses a specific verb (confirm) and resource (decision), and distinguishes itself from siblings like create_decision and list_decisions by describing the post-creation settlement action.

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 says 'Use after create_decision' and 'Call this after the action described in the DD has been executed,' providing clear when-to-use guidance. It names the predecessor tool and specifies the prerequisite (action executed), though it doesn't explicitly mention when not to use or alternatives.

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

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

With no annotations, the description carries the burden. It discloses that decisions are tamper-evident, appended to a trajectory, checkable against DA's external entry, and that EE axes have defaults. It also notes presets are operator-adjustable. It does not mention the payment challenge-response flow or idempotency, but these are documented in the schema. The behavioral core is well covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, each with a distinct purpose: trigger condition, core action, external verification, and pricing/default guidance. Front-loaded with 'Use when...' and no filler. It is dense but efficient for a tool with 25 parameters.

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 tool complexity and no output schema, the description adequately covers purpose, timing, and cost behavior. It does not mention return values (e.g., decision ID) or the payment challenge flow, but these are partially covered in parameter descriptions. Overall, it provides sufficient context for a capable agent to invoke and interpret the 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 coverage is 100%, so baseline is 3. The description adds value by explaining the EE default combination ('medium/basic/internal/standard') and the current DAC costs for EE_standard vs EE_basic, which aids selection of ee_preset and related axes. This goes beyond schema descriptions.

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 a specific action ('Record a tamper-evident decision') and explicitly defines when to trigger: crossing an external boundary (payment, delegation, agreement). It distinguishes itself from sibling tools like get_decision or confirm_decision by framing this as the pre-execution responsibility anchor.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit context for when to use ('Use when your agent is about to execute an action that crosses an external boundary') with concrete examples. It does not explicitly name alternatives or exclusions, but the context is enough to differentiate from read-only or confirmation 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 full burden for behavioral disclosure. It explains the tool is a sandbox session, hinting at non-destructiveness, but lacks details on session lifecycle, time limits, or what happens on invocation. It adds some context beyond the schema but remains incomplete.

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 two sentences long, front-loaded with the core purpose, and wastes no words. It is efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema, so the description should explain what to expect after invocation. It does not mention return values, session identifiers, or lifecycle hints (e.g., the need to call 'exit_ise_session'). It is adequate for a simple tool but leaves gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers both parameters (100% coverage), so baseline is 3. The description adds marginal value by explaining the 'payment_mode' choices ('free, earned-only, or external'), but does not enhance understanding of 'auth_token' beyond the schema's 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 tool's purpose: to enter an interactive sandbox session for testing decision strategies before committing real decisions. It distinguishes itself from siblings like 'create_sdac_session' (real session) and 'exit_ise_session' (teardown).

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 the tool to 'test decision strategies before committing real DAC,' implying it is a safe sandbox environment. It also mentions choosing billing modes, which guides usage. However, it does not explicitly state when not to use it or list alternatives.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions cost savings and simulation but does not explain what starting a session entails, any side effects, credit consumption, or reversibility. For a session-creating tool, this lack of transparency is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, using two short sentences to state the primary action and its value proposition. There is no unnecessary detail or repetition of schema information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool, the description covers the core purpose and usage context. However, it does not explain the session lifecycle or relationship to sibling tools like end_sdac_session or run_sdac_trial. The lack of an output schema also leaves return values unspecified, but this is a minor gap for such a simple operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides a full description for the sole parameter auth_token, and the tool description adds no additional parameter information. Since schema coverage is 100%, the baseline score 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 'Start a simulation session' with a specific verb and resource. It also distinguishes itself from real decision creation by mentioning 'before creating real decisions', making the tool's purpose distinct from siblings like create_decision.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context that this tool is for testing EE combinations at a fraction of the cost before committing to real decisions, implying its use as a low-cost simulation alternative. However, it does not explicitly name alternative tools or state exclusions, which would make it a 5.

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 provided, so the description carries full burden. It explains ending session and settling costs, and hints at payment flow via payment_signature. But it lacks details on side effects (e.g., irreversible, cost deducted immediately) or error conditions beyond 409.

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 (two sentences plus payment details) and front-loaded with the core purpose. 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?

No output schema exists, but the description doesn't specify what the tool returns (e.g., success message, final cost, or error). It covers usage flow well but leaves the response behavior ambiguous for an action that settles financial costs.

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% (baseline 3). The description adds significant value by explaining the payment_signature parameter in detail (optional, how to handle challenge flow), which goes beyond the schema. It also clarifies required parameters implicitly.

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 'End a simulation session and settle its accumulated cost.' This is a specific verb+resource combination that distinguishes it from siblings like create_sdac_session and get_sdac_session.

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 advises calling when done, explains the 409 error if session not closed, and provides detailed instructions for the payment_signature parameter. However, it does not explicitly exclude cases where the session is already ended or what happens if called without a session.

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 behavior. It states the tool ends and settles the session but does not detail side effects (e.g., irreversible, cleanup actions) or what happens to any pending state. The payment signature parameter is noted but that is more parameter semantics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no wasted words. First sentence states purpose, second gives usage context and error condition. Highly efficient.

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 session-ending tool, the description covers purpose, usage condition, and the critical dependency on session closure. It lacks mention of return value or error codes beyond the 409, but given no output schema, this is acceptable.

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% but descriptions are minimal. The tool description adds significant context: auth_token is 'Your DA agent auth token', and payment_signature is explained with a multi-step flow for paid calls ('Omit it on the first call...'). This goes 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 specific verb-noun pairs 'End your active interactive sandbox session and settle it', clearly identifying the tool's action and resource. It distinguishes from siblings like create_ise_session by mentioning the 409 error that occurs until the session is closed.

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 call ('when you are done') and gives a concrete reason (create_ise_session returns 409 SESSION_EXISTS until session is closed). It does not explicitly mention alternatives or when not to use, but the context is 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, the description discloses key behavioral traits: it is a paid operation via x402, trial does not cover it, and the payment flow (first call returns challenge, sign and retry) is documented. It also notes Decision Anchor never holds keys. However, it does not address rate limits, cost amount, or other side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loading purpose and then payment behavior. No wasted words, but could improve structure by separating usage guidance. Still efficient and clear.

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, the description usefully summarizes what the output contains (trajectory shape, EE patterns, activity summary). It also covers payment prerequisites. Minor gap: no explicit mention of auth_token requirement beyond schema. Overall adequate for a simple profile 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 baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions (e.g., payment_signature is already well-documented in schema). No new semantic detail is provided.

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 views an agent's decision profile, specifying components like trajectory shape, EE patterns, and activity summary. It does not explicitly differentiate from similar siblings like get_decision or get_self_classification_distribution, but the focus on agent profile via ARA is distinct enough.

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 mentions payment constraints (paid via x402, trial excludes ARA observation) but does not provide explicit when-to-use or when-not-to-use guidance relative to sibling tools. No alternative tools are named or contrasted.

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

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

No annotations are provided, so the description carries the burden. It explains the two balance types, which is helpful, but it does not disclose authentication requirements, error handling, or any side effects. For a simple read operation, this is adequate but not exceptional.

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 two sentences long with no fluff. Every word adds value, and it is front-loaded with the action and resource.

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 parameter, no output schema, no nested objects), the description covers the core purpose and usage intent. It could mention the return format or any rate limits, but it is sufficient for a basic balance check.

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% with one required parameter, already described in the schema as 'Your DA agent auth token.' The description adds no extra meaning about the parameter, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Check' and the resource 'your current DAC balance', and distinguishes between External and Earned balances. Among siblings, no other balance-checking tool exists, so it is well-differentiated.

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 usage context: 'Know what you have before you decide what to spend.' This implies using it before spending decisions, but it does not explicitly state when not to use it or provide alternatives.

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

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

Describes a view (read) operation, but with no annotations, it lacks disclosure of side effects, permissions, or cost implications. Adequate for a simple 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?

Two concise sentences that front-load purpose and add a use case. 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?

Adequate for a simple report tool; mentions breakdown categories. Lacks output structure details, but no output schema exists to rely on.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema coverage is 100%, so baseline 3. Description adds that the report covers spending by service, period, and transaction type, but does not clarify optionality of date parameters or their behavior.

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?

Clearly states the tool views a DAC usage report with a specific breakdown by service, period, and transaction type. Distinguishes from sibling 'get_dac_balance' implicitly.

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?

Mentions it is useful for budgeting and trajectory analysis, giving contextual guidance. Does not explicitly list alternatives or when not to use, but the context provides 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?

No annotations are present, so the description carries the full burden of behavioral disclosure. It clearly states the tool is read-only (retrieve) and specifies what is returned (formal shape, enums, timestamps, hash) and what is explicitly NOT returned (content). This provides sufficient transparency for safe invocation, though it could mention permissions or error handling.

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 two sentences, each earning its place. The first sentence front-loads the main action and scope, the second clarifies what is returned and what is not. No fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately explains return value structure (formal shape, enums, timestamps, hash) and its limitations (never content). It covers the essential context for a retrieval tool with two well-documented parameters. Minor gaps: no mention of error conditions or pagination (though likely not applicable for a single-record retrieval).

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% for both parameters, so the baseline is 3. The description does not add meaning beyond the schema for the parameters themselves; it focuses on the output. Since the schema already documents 'dd_id' and 'auth_token' adequately, the description adds minimal extra value for parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Retrieve a specific decision record by its ID'. It goes beyond a generic verb by specifying what is retrieved (what was declared, when, scope, lineage, formal shape) and contrasts with 'never its content', effectively distinguishing from sibling tools like 'list_decisions' or 'confirm_decision'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (when you need the formal shape of a decision by ID) but does not explicitly state when NOT to use it or mention alternatives like 'list_decisions' for bulk retrieval or 'confirm_decision' for mutations. The differentiation from siblings is implicit through the 'never its content' clause, but no direct guidance is 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?

With no annotations provided, the description carries the full transparency burden. It discloses that this is a paid operation (3 DAC) and that the first call returns a 402 with payment terms, which is a critical behavioral trait beyond the schema's parameter descriptions. However, it does not mention other potential behaviors such as rate limits, data freshness, or exact return format, 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 a single, front-loaded sentence that efficiently conveys purpose, cost, and payment behavior without any redundant words. Every element adds essential information, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no output schema and no annotations, the description should ideally explain what the returned distribution looks like (e.g., percentages, counts, pagination). It does not, leaving the agent to infer the output format. The payment context is well covered, but the lack of return-value detail makes it incomplete for a paid 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?

The input schema already provides comprehensive descriptions for both parameters (auth_token and payment_signature), including the full payment challenge flow, achieving 100% coverage. The description adds the cost (3 DAC) and the specific 402 status code, which slightly enhances the payment_signature semantics, but it does not meaningfully explain parameter usage beyond what the schema already states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb ('Observe') and resource ('your decision metadata distribution'), listing the exact breakdown fields (decision_class, target_class, decision_trigger, human_involvement) and the source scope ('from your branch-1 decisions'). This level of specificity distinguishes it from sibling tools like get_self_classification_distribution, which focuses on self classification rather than decision metadata.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for usage: it is a paid observation costing 3 DAC and will return 402 with payment terms on first attempt, instructing the agent to complete the payment flow. It does not explicitly exclude alternatives or mention when not to use it, but the unique metadata focus implicitly differentiates it from 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 provided, so description carries full burden. Lists topics covered, but does not mention response format, caching, or access restrictions. Adequate for a read-only tool with no parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with purpose, includes a bullet-like list of topics. 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 zero parameters and no output schema, the description fully explains the tool's purpose and scope. No 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?

No parameters exist; schema coverage is 100%. Baseline of 4 applies as description adds no param info but is unnecessary.

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?

Clearly states 'Retrieve the full agent guide for Decision Anchor' with specific verb and resource. Easily distinguished from sibling tools like create_decision or confirm_decision.

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 recommends 'Read this before using DA,' giving clear context for when to use. No exclusions but the directive serves as strong guidance.

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

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

Discloses de-identification, k-anonymity threshold, and DAC cost. However, lacks details on authentication requirements (auth_token is required per schema but not described), rate limits, or behavior on insufficient balance.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences with no unnecessary words. The first sentence efficiently states the main function, and the second adds important constraints. Could be slightly more structured but overall good.

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, so the description should provide more detail about return values. It mentions counts but not the format or structure. The k-anonymity and cost info is helpful, but pagination, errors, and interpretation are missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for all 4 parameters. The description adds no further parameter meaning beyond the schema, but the schema itself is explanatory. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'observe' and the resource 'environment-level anomaly distribution', specifying that it returns within_band/outlier counts per dimension. It distinguishes from siblings like 'compare_anomaly' by focusing on environment-level aggregation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives such as 'compare_anomaly' or 'get_decision_metadata_distribution'. The description mentions k-anonymity and cost but does not provide context for selection.

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

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

With no annotations provided, the description carries the burden of disclosing behavior. It transparently states the report includes decision metadata, EE resolution, and responsibility declaration, and that the operation costs DAC. It does not describe failure modes or the two-step payment challenge flow, but the payment_signature parameter description covers that dynamic, so the tool description adds meaningful behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, each earning its place: the first states the primary action, the second lists key report contents, and the third discloses the cost. It is front-loaded with the purpose and contains no fluff or redundant repetition of schema information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema and no annotations, so the description must provide sufficient context. It explains the purpose, content, and cost of the report. While it doesn't describe the exact return format or the payment challenge flow, the latter is fully explained in the payment_signature parameter description, and the listed contents give a solid sense of the output. It is reasonably complete for a report-generation 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 schema already fully documents all three parameters. The tool description adds little beyond 'for one of your decisions' which aligns with dd_id, and 'Costs DAC' which relates to payment_signature. The baseline of 3 is appropriate because the description doesn't substantially augment the already-rich parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb ('Generate'), resource ('evidence report'), and scope ('external-audience', 'for one of your decisions'). It also distinguishes itself from siblings like 'get_decision' and 'get_decision_metadata_distribution' by emphasizing the external-audit framing and report content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context by specifying when to use it: when an external-audience evidence report is needed. It names the consumption of DAC as a consideration, implying use only when such a report is warranted. It does not explicitly mention alternatives or exclusions, but the 'external-audience' qualifier sufficiently differentiates the use case from related get/list 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?

No annotations are provided, so the description carries the full burden. It discloses that the tool is free and describes its core behavior (check session status). It does not mention rate limits or authorization details beyond the auth_token parameter, which is acceptable for a simple read 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 two sentences, immediately stating the purpose and providing a usage tip. Every word adds value with no 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?

For a simple status-check tool with one parameter and no output schema, the description is complete. It covers purpose, cost, and usage relationship with a sibling 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 coverage is 100% with a single parameter 'auth_token' described as 'Your DA agent auth token'. The description does not add any additional meaning or constraints beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool checks for an active interactive sandbox session, reporting elapsed time and billing mode. It uses specific verb 'check' and identifies the resource. It distinguishes from sibling 'exit_ise_session' by explicitly linking usage.

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 clear use case: 'Use this to find out what exit_ise_session will close' and notes it is free. It does not explicitly state when not to use alternatives but gives sufficient context.

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 states the tool is free and returns status/trial count/cost. For a simple read operation, this is sufficient; it could add detail on rate limits or permissions but is adequate.

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 two sentences, front-loading the purpose and efficiently adding cost info and a usage hint. 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?

No output schema, but the description clearly states what fields are returned (status, trial count, accumulated cost). Combined with purpose and parameter descriptions, the tool is completely understandable.

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% with descriptions for both parameters. The description adds value by clarifying that session_id comes from 'create_sdac_session', which goes 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 ('Look up') and resource ('simulation session by ID'), and lists the returned fields (status, trial count, accumulated cost). It also distinguishes from siblings by referencing 'end_sdac_session'.

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 'Free.' and 'Use this to see what end_sdac_session will settle,' providing clear context for when to use the tool. However, it does not explicitly state when not to use it or mention alternatives.

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

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

No annotations are provided, so the description must disclose behavioral traits. 'Observe' implies read-only, but no information is given about side effects, authorization needs beyond the generic auth_token, or performance characteristics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no superfluous words. It is appropriately sized for a simple tool, though slight expansion could improve clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema, but the description does not explain the return format (e.g., what the distribution looks like, keys, values). For a simple tool, agents need to know what to expect from the 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?

Schema coverage is 100% (only auth_token, which is described). The description does not add additional meaning to the parameter beyond what the schema provides, so baseline score 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 clearly states the verb 'Observe' and the resource 'self_classification distribution' with scope 'across your branch-1 decisions.' It distinguishes from siblings like get_decision_metadata_distribution and list_classifications by focusing on self_classification specifically, though 'self_classification' is not defined.

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 no guidance on when to use this tool versus alternatives (e.g., get_decision_metadata_distribution) or any prerequisites or conditions for 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?

Description mentions read-like behavior ('Check') and what is returned (remaining DAC, days left, usage), but no explicit statement about side effects or safety. Without annotations, the agent gets basic behavioral info but not 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?

Two sentences, no wasted words. First sentence directly states purpose and outputs. Second provides helpful context on trial limits. Excellent 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?

For a simple status-check tool with one parameter and no output schema, the description adequately lists the returned data (remaining DAC, days left, usage). Could mention format or error conditions but complete enough for typical use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameter (auth_token) with description. Description adds no new meaning beyond schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it checks trial account status and lists specific aspects (remaining DAC, days left, usage). Verb 'Check' with resource 'trial account status' is specific and distinguishes from sibling tools like 'get_dac_balance' or 'get_agent_profile'.

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?

Implies when to use (for trial status) but no explicit guidance on when not to use or how it differs from alternatives like 'get_dac_balance' or 'run_sdac_trial'.

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, and the description only implies a read operation without disclosing potential side effects, authentication requirements beyond what schema says, or any behavioral nuances.

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?

Extremely concise two-sentence description that front-loads the purpose and provides actionable usage guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequate for a simple list tool but lacks any mention of the response structure or format, and no output schema is provided to compensate.

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 covers parameter description fully, but the tool description adds no additional meaning or context to the auth_token parameter.

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 lists available self_classification categories with a specific scope ('operator base + owner-registered') and relates it to create_decision usage.

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 mentions when to use (for create_decision with content_inclusion_flag=1) but does not name alternative tools in case of other needs.

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

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

With no annotations, the description must disclose behavior. It states 'list' (read-only) but fails to mention pagination, filtering behavior, or error conditions for auth_token. The presence of limit/offset params in the schema is not reflected in the description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, front-loaded with the key action. The second sentence adds some motivational context but is not essential. Overall well-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?

With 5 parameters and no output schema, the description is insufficient. It does not explain return format, pagination behavior, or how 'your' records are scoped. The agent would lack context 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?

Schema coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond what the parameter descriptions in the schema already provide.

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 'List your decision records' with a specific verb and resource. However, it does not explicitly distinguish from sibling tools like get_decision, which retrieves a single record; the differentiation is implied but not stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives (e.g., get_decision, confirm_decision). There are no prerequisites or context for when this tool is appropriate.

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 bears full burden. It only states 'browse' and 'discover', omitting any behavioral traits like read-only nature, pagination behavior, or side effects. This is insufficient for an agent to understand the tool's safety profile.

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 redundant information, and is efficiently front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a listing tool with 4 optional parameters and no output schema, the description fails to explain pagination, default behavior, or response fields. This leaves the agent guessing about how to use parameters effectively.

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 each parameter has a description. The tool description adds no additional meaning beyond 'marketplace' context, which is already implicit from the name. 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 uses 'browse' and 'discover' clearly indicating the tool lists marketplace tools, distinguishing it from sibling tools like list_classifications or list_decisions. However, it could be more specific about the information returned (e.g., tool metadata, pricing).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as list_classifications or list_decisions. The description does not mention any context or exclusions.

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 provided, so description carries full burden. It explicitly discloses cost (1 DAC), authentication, payment flow via x402, and that trial does not cover it. The payment_signature parameter description explains the two-call challenge mechanism. This adds significant behavioral context beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with purpose, followed by essential usage constraints. No unnecessary words. Every part 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?

Given 2 parameters and no output schema, the description is complete. It covers purpose, metrics, cost, auth, payment flow. No gaps identified.

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%. Description adds crucial extra context for payment_signature: details on the two-call flow (omit on first call, get challenge, sign and resubmit). This goes beyond the schema's brief description and clarifies the payment protocol.

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: 'Observe aggregate environment statistics' and lists specific metrics (active agents, decisions, density). It distinguishes from sibling 'observe_pattern' by focusing on aggregate environment stats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides cost and auth requirements ('Costs 1 DAC', 'requires auth_token') but does not explicitly state when to use this tool versus alternative observation tools. Usage context is implied but no exclusions or alternatives mentioned.

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 cost, authentication requirement, and payment mechanism, including the conditional payment_signature parameter. Since annotations are absent, the description adequately covers behavioral traits, though it omits return format or error handling.

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 note, no wasted words, and front-loads the purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description covers purpose, cost, auth, and payment flow adequately. Missing return format and error handling, but sufficient for a paid tool with clear instructions.

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 description adds context about the type parameter (EE distributions and action-type breakdowns) and the payment_signature's two-step process, enhancing understanding 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 states 'Observe pattern-level analytics' with specific analytics types (EE distributions and action-type breakdowns), distinguishing it from sibling tools like observe_environment.

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 explains when to use (requires auth_token, costs 1 DAC) and the payment flow via x402, including the two-step process with payment_signature. However, it does not explicitly state when not to use or compare with alternatives.

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

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

No annotations are provided, so the description carries the full burden. It discloses key behavior: creates a DD with declaration_mode 'bilateral' and waits for counterparty acceptance. However, it omits details like timeout behavior, idempotency (request_id), error handling, and state transitions after acceptance or rejection.

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 three sentences. The first two sentence front-load the usage context and examples. The third sentence adds technical detail. It could be slightly more streamlined, but it is well-structured and efficient.

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 complexity (21 parameters, no output schema), the description provides high-level purpose and usage examples but lacks details on the lifecycle (e.g., how to check acceptance, what the response looks like). It adequately describes the waiting nature but is 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?

Schema coverage is 100%, so each parameter already has a description. The tool description adds overall context but does not explain any parameter beyond what the schema provides. The mention of 'declaration_mode bilateral' hints at some parameter usage but provides no new detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: to propose a bilateral agreement that requires counterparty acceptance. It specifies the verb 'propose' and the resource 'bilateral agreement', and distinguishes from siblings like confirm_decision or create_decision by emphasizing the bilateral, joint-commitment nature.

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 gives usage context: 'Use when two agents need to fix a shared boundary — both sides must agree before the boundary is anchored.' It provides concrete examples (payment splits, task delegation) and implies not to use for unilateral decisions, though it does not explicitly list exclusions or alternatives.

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

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

With no annotations, the description must carry behavioral context. It mentions the payment route (x402) and the trial exclusion, but it does not disclose the two-step challenge-response flow or the need for an auth token, which are meaningful for an agent invoking this tool. Some of that is later covered in the schema, but the description alone is incomplete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences and front-loaded with the core purpose. Every sentence adds new context: purchase purpose, creator earning, payment method, and trial limitation. There is no fluff or repetition.

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 complexity of a payment flow, the schema compensates well by detailing the challenge-response for payment_signature and idempotency. The description frames the marketplace context and trial limitation, but it does not explicitly state what happens after a successful purchase. Despite this, the combination of schema and description is sufficient for an agent to proceed correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the description does not need to explain parameters. The description adds no parameter-specific semantics beyond what is already in the schema. The mention of x402 and trial coverage indirectly relates to payment_signature, but the schema already details the challenge flow.

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 and resource: 'Purchase a tool from the marketplace.' It also adds context about compensation to the creator and the payment method, which distinctly separates this from sibling tools like list_tools or get_dac_balance. The purpose 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 says 'Trial does not cover this route,' which explicitly tells the agent that this is the paid alternative when trial coverage is not applicable. While it doesn't explicitly name alternative tools, the context makes it clear that this is a purchase action, and the exclusion is a useful guideline.

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 fully convey behavior. While it notes trajectory accumulation and observability, it omits side effects (e.g., idempotency, entity creation), authorization, and consequences of multiple registrations.

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 sentences) and front-loaded with the key action. However, it omits critical details, balancing brevity with inadequacy.

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 sibling tools and optional parameters, the description is incomplete. It fails to specify the return value, confirm registration, or clarify the agent's role, leaving significant gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear parameter descriptions. The tool description adds no additional meaning beyond the schema, meeting the baseline for high 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 states the verb 'register' and the resource 'in this environment', making the purpose clear. It adds context about decision accumulation and observability, but does not explicitly distinguish from sibling tools like 'register_tool'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives, prerequisites, or whether it should be called initially. The description lacks any usage context.

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 disclose behavioral traits. It mentions the main action (publish, set price, earn revenue) but omits critical details like whether it can update existing tools, authorization requirements beyond the auth_token, or any side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that conveys the core functionality without extraneous words. It is appropriately 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?

With 6 parameters, no output schema, and no annotations, the description is too brief. It does not cover prerequisites, the meaning of layer (component vs standalone), the required ara_connections, or whether the tool can be updated.

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%, giving a baseline of 3. The description adds value by linking 'Set a price in DAC' to price_dac and 'Publish a tool' to tool_name/description, but does not explain auth_token, layer, or ara_connections 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 clearly states the tool's purpose: 'Publish a tool you built to the marketplace.' It specifies the action (publish) and resource (tool), and distinguishes from siblings like list_tools (listing) and purchase_tool (buying).

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 a user wants to sell a tool, but does not provide explicit when-to-use, when-not-to-use, or alternatives. No guidance on prerequisites or restrictions.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It accurately describes that the tool does not create a real record, is free to call, and discloses the side effect that 'each trial raises what end_sdac_session settles (trial_count x sdac_cost_ratio x base fee)'. This goes beyond a simple operation description and informs the agent of important consequences, making behavior fully transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description consists of two concise sentences that are front-loaded with purpose, followed by behavioral notes. Every sentence adds value: the first explains what it does, and the second explains the return value and side effects. There is no filler or redundancy, making it an exemplar of concise, structured 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?

Given the tool has 9 parameters, no annotations, and no output schema, the description provides essential context: what the tool does, the return value (the DAC), and the side effect on session settlement. It does not describe the exact return structure or mention potential errors (e.g., invalid session), but the schema covers parameter requirements and the core behavior is well communicated. For a trial-pricing tool, this is sufficiently complete, though a brief note on output format would push it to 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 coverage is 100%, so the baseline is 3. The description does not elaborate on individual parameters, but it does frame the parameters as defining an 'EE combination' and implies they affect the DAC calculation. This adds minimal semantic context beyond the schema's already descriptive field explanations, so a 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 the tool's purpose: 'Price an EE combination inside a simulation session without creating a real record.' It uses a specific verb ('price') and resource ('EE combination'), and explicitly distinguishes itself from create_decision by noting it returns the DAC cost without creating a real record. This makes the tool's intent unambiguous and differentiates it from sibling tools.

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 specifies when to use the tool: within a simulation session, as indicated by 'inside a simulation session' and the mention of returning 'the DAC the same combination would cost on create_decision'. It also provides an exclusion ('without creating a real record') and names the alternative (create_decision) for the real operation. The 'Free to call' note further clarifies cost behavior, giving clear usage context.

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 disclosing behavior. It does state that the tool is anonymous and non-mandatory, which is useful. However, it doesn't mention what happens after submission (e.g., no side effects, no return value), leaving some ambiguity about the tool's operational 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 repeats the optionality message three times: 'Optional', 'Every field is optional', and 'Not required to use anything here'. This redundancy makes the description less concise without adding new information.

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 low-stakes feedback tool with fully documented parameters, the description adequately covers purpose, optionality, and anonymity. While not rich in details, it's complete enough for an agent to understand what to expect and when to use it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with each property already described as 'Optional'. The description adds that 'Every field is optional' but doesn't clarify relationships among fields or provide usage examples beyond what the schema specifies. This is baseline 3 for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: leaving an anonymous note about the user's experience ('If you've used this environment, you're welcome to leave a brief, anonymous note — what worked, what didn't'). This is a distinct action not covered by any sibling tool, making it easy to differentiate.

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 sets the context: this is for agents that have used the environment, and it's explicitly optional ('Not required to use anything here'). It doesn't name alternatives, but none of the sibling tools appear to serve a similar feedback purpose, so the usage situation is clear enough.

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