Decision Anchor

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

No annotations are provided, so the description carries the burden. It usefully discloses the return shape (band_position with within_band/outlier for 5 dimensions) and the cost implication ('Costs DAC'). It does not explicitly state whether the tool is non-mutating, though 'Compare... Returns...' implies a read-only 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 two sentences with no filler. The first sentence states the purpose and scope, and the second provides the key output and cost information. 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?

Given that there is no output schema, the description adequately covers the return concept and dimensions, and it mentions the cost. The parameter semantics are fully handled by the schema. It could add more about error conditions or side effects, but for a simple comparison tool, it 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 already documents all four parameters with meaningful descriptions, including the payment challenge flow for payment_signature. Since schema description coverage is 100%, the baseline of 3 applies; the description adds no parameter-level detail 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 the tool's operation: comparing one of your decisions against your accumulated pattern, and specifies the output (band_position for five named dimensions). However, it does not explicitly differentiate itself from sibling tools like get_environment_anomaly or 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?

The description implies the use case—checking whether a decision is anomalous relative to your accumulated pattern—but it provides no explicit when-to-use guidance or alternatives. It says what the tool does, but not when to choose it over related tools like get_environment_anomaly.

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 states the effect: 'the agreed scope is fixed outside both parties' own logs' and 'marks the anchored declaration as settled.' It also clarifies that the integrity hash and timestamp are created at declaration time (create_decision) and confirm only needs the dd_id, explaining the tool's dependency and non-recreation of metadata. It does not explicitly state irreversibility, but 'fixed' implies permanence. It omits return format and error behavior, but for a simple settle action, this coverage 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 three sentences with some redundancy: 'Use after create_decision to settle the anchored boundary as an external record' and 'Confirm a pending decision: marks the anchored declaration as settled' convey overlapping information. It could be tightened to two sentences without losing meaning. The key usage context is front-loaded, but the repetition slightly detracts from 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 two-parameter tool with no output schema, the description covers the essential context: when to call (after create_decision and action execution), what it does (settles and fixes scope), and the minimal input (dd_id only). It does not describe return values or failure modes, but given the tool's simplicity and the 100% schema coverage, this is adequately 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?

Schema description coverage is 100%, so the baseline is 3. The description adds context that only dd_id is required and that it references an existing declaration, which is helpful. However, it does not explain the format or where to obtain dd_id, and auth_token is not discussed beyond the schema. The added value over the schema is marginal but present.

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 confirms a pending decision by marking the anchored declaration as settled, with a specific verb ('confirm') and resource ('decision'). It implicitly differentiates from create_decision by referencing it as the prerequisite, and from get_decision by focusing on the settlement action. However, it does not explicitly name sibling alternatives, which would strengthen differentiation.

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 timing guidance: 'Use after create_decision' and 'Call this after the action described in the DD has been executed.' This tells the agent when to invoke it in the workflow. It does not mention when not to use it or alternatives, but the sequencing is clear and actionable.

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 behavioral burden. It discloses that the decision is tamper-evident, added to a record trajectory, and that omitting EE axes applies defaults. It also mentions pricing and preset adjustability. It does not explicitly state mutation or irreversibility, but 'Record' and 'tamper-evident' imply persistence. It lacks some details like idempotency or payment flow, but those are covered in parameter descriptions.

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 dense paragraph, reasonably front-loaded with the when-to-use guidance. However, it packs several topics (purpose, timing, alternative, record trajectory, pricing, presets) into one block, making it slightly verbose. It could be broken into clearer sections, but it is not excessively long.

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 tool with 24 parameters, a nested object, and no output schema, the description covers the core usage, the key alternative, pricing implications, and record persistence. It does not explain the return value or the content_inclusion_flag branches, but those are detailed in parameter descriptions. Given the complexity, it is sufficiently complete for an agent to invoke 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 baseline is 3. The description adds value beyond the schema by explaining EE presets, default costs (45 DAC vs 10 DAC), and how omitting EE axes maps to the EE_standard preset. This is not present in the schema and helps the agent estimate costs and understand defaults.

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 records a tamper-evident decision when an action crosses an external boundary (payment, delegation, or agreement). It explicitly differentiates from propose_bilateral for counterparty declarations, so an agent knows exactly what this tool does and how it differs from its closest sibling.

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

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

The description provides explicit when-to-use guidance: 'Use when an action crosses an external boundary' and specifies timing ('before you execute, or after a decision you have already made'). It also names the alternative (propose_bilateral) and the condition that selects it (counterparty involvement), leaving no ambiguity.

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 does disclose an important trait—'Content is not recorded'—and clarifies that the session makes no decision/accountability demands. But it omits lifecycle details, side effects, permission needs, return values, or how the session is later exited, leaving meaningful behavioral 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?

Two short sentences with no filler. The purpose is front-loaded, and every clause adds information: the state type, the missing obligations, the recording behavior, and the billing choice.

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 (two optional parameters, no nested objects, no output schema), and the description covers the core semantics. However, it doesn't mention what the tool returns, what an ISE session is, or how/why one would leave it. An agent could invoke it correctly but would be guessing about lifecycle and billing implications.

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 auth_token and payment_mode. The description only restates the billing choice ('free, earned-only, or external') without explaining what those modes mean or affecting how either parameter is used. This matches the baseline for high schema coverage.

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

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

The description states a clear action and resource: it creates/enters a non-productive state where no decision, execution, or accountability declaration is required. It also adds meaningful scope by saying content is not recorded. It doesn't explicitly distinguish itself from siblings like create_sdac_session or exit_ise_session, and 'ISE' is never expanded, so it falls just short of 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?

The description implies when to use the tool: whenever a non-productive state is desired and no decision/execution/accountability is needed. However, it gives no explicit when-not-to-use guidance and never points to alternatives such as exit_ise_session or create_sdac_session, so usage context is only partially 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 carries the full burden of behavioral disclosure. It does not mention session lifecycle (e.g., that end_sdac_session exists), side effects, statefulness, or what happens after creation. The description only gives purpose and cost savings, leaving the agent uninformed about consequences.

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 fluff, the primary action is front-loaded, and every word contributes to clarifying the tool's role. Efficient and well-structured.

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

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

For a simple session-creation tool with one optional parameter and no output schema, the description covers the core purpose but omits how the session integrates with sibling tools (run_sdac_trial, end_sdac_session) and what constitutes a successful outcome. Adequate but with room to improve.

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 the only parameter (auth_token), which is thoroughly described. The description adds no additional parameter insights, so the baseline of 3 is appropriate since the schema already handles the semantics.

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

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

The description states a specific verb and resource ('Start a simulation session') and clearly explains its purpose: testing EE combinations at low cost before creating real decisions. This distinguishes it from create_decision and other sibling tools without opening schemas.

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 implies when to use the tool ('before creating real decisions') but does not explicitly mention alternatives or exclusions like create_ise_session. The context is clear enough for an agent to infer the testing use case, though it could be more 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 provided, the description carries the behavioral disclosure burden. It reveals that the session is ended and accumulated cost is settled, and that an unclosed session blocks creation of a new one via a 409. The schema adds detail about the payment challenge flow. It could mention idempotency or whether the action is reversible, but the core side effects are disclosed.

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

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

Three short sentences with no filler. The core purpose is front-loaded, the trigger is stated next, and the key side effect is included. Every sentence earns its place.

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

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

For a session-ending tool, the description plus rich schema coverage gives an agent enough to call it correctly. There is no output schema and no mention of what the response looks like or whether the call is idempotent, but those are minor gaps given the simplicity and the strong schema content.

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%, and the schema thoroughly documents all three parameters, including the payment_signature first-call/challenge/retry flow. The description does not add parameter-level detail, but the baseline of 3 applies because the schema already carries the meaning.

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: 'End a simulation session and settle its accumulated cost.' It clearly distinguishes this from sibling tools like create_sdac_session and get_sdac_session by focusing on termination and cost settlement.

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 explicitly says 'Call this when you are done,' giving a clear trigger for use. It also provides a useful consequence: until the session is closed, create_sdac_session returns 409 SESSION_EXISTS. It does not name an alternative tool, but the action is sufficiently distinct that none is required.

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. It discloses that the session is ended/settled and that creating a new session is blocked until then, which is useful. However, it does not explain what 'settle' means, whether the operation is idempotent, what errors may occur, or what the response looks like.

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

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

Three short sentences, each adding distinct value: the core action, the when-to-call guidance, and the key consequence. The description is front-loaded with the most important information and contains no filler.

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

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

For a tool with no annotations and no output schema, the description gives the essential usage context and a critical behavioral consequence. However, the ambiguous 'settle it' and the lack of response/error behavior leave an agent uncertain about what to expect after calling the tool, especially given the optional payment_signature parameter.

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%, and the input schema already provides detailed explanations for auth_token and payment_signature, including the payment challenge flow. The description adds no parameter-specific meaning, so the baseline score of 3 applies.

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

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

The description clearly states a specific action ('End your active ISE session') on a specific resource (ISE session), and 'ISE' distinguishes it from the SDAC session tools. However, 'settle it' is vague and does not clarify whether this is a financial settlement, session finalization, or both.

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 'Call this when you are done' and gives a concrete consequence: 'create_ise_session returns 409 SESSION_EXISTS' until the session is closed. This provides a clear when-to-use signal, though it does not mention when not to use it or explicitly compare with end_sdac_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?

With no annotations, the description carries the behavioral burden. It discloses that the operation is viewed rather than mutating, that it incurs x402 payment, and that Trial access is insufficient. It does not elaborate on rate limits or side effects, but for a read-oriented profile tool the payment disclosure is the key behavioral constraint.

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 filler. The purpose is front-loaded and the critical payment constraint is stated immediately after, making the essential information 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 description names the expected result components (trajectory shape, EE patterns, activity summary), which partially compensates for the missing output schema. Payment prerequisites and parameter details are covered by the schema, so an agent has enough context to invoke the tool correctly.

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

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

Schema description coverage is 100%, so the schema already documents agent_id, auth_token, and payment_signature in detail. The description adds context about the returned profile content but does not materially deepen the meaning of the individual parameters 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?

Description uses a specific verb ('View') and a specific resource (agent's decision profile), then details what the profile contains: trajectory shape, EE patterns, and activity summary. The 'as observed through ARA' qualifier distinguishes this from similar-looking observational 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 clearly conveys the key usage condition: this is a paid x402 operation and Trial does not cover ARA observation. It gives the agent enough context to know when this tool applies, though it does not explicitly name alternative tools or state when to avoid 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, the description carries the behavioral burden. It indicates a read-only check and spells out the two returned balance categories, but it does not explicitly state that there are no side effects, how authentication is resolved, or the exact return shape.

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 short sentences with the core action front-loaded followed by useful context. No filler or redundant repetition of the tool name.

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 balance-check tool with one optional parameter, the description conveys what is checked, the two balance categories, and why it matters before spending. Minor gaps are the absence of an explicit read-only/no-side-effect statement and no mention of units or formatting, but nothing critical is 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% and the single optional auth_token parameter is thoroughly described in the schema, including precedence rules. The description adds no parameter-specific detail, so the schema-heavy baseline applies.

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

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

The description uses a specific verb-resource pair ('Check your current DAC balance') and clarifies the two balance components: External (funded) and Earned (from tool sales). It is clear, but it does not explicitly differentiate from related siblings such as get_dac_ur, leaving some differentiation implicit.

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 line 'Know what you have before you decide what to spend' gives clear context for when to call the tool, tying it to spending decisions. It does not name alternatives or state when not to use it, but the intended context is evident.

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 responsibility for behavioral disclosure. It uses 'View' which implies read-only, but it does not explicitly state that no data is modified, whether authentication is required beyond the token parameter, or any other behavioral traits. The description is too sparse to fully disclose 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 two sentences with no wasted words. The core purpose is front-loaded, and the second sentence adds relevant context. Every phrase 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, so the description partially compensates by describing the report contents ('breakdown of spending by service, period, and transaction type'). However, it does not mention the return format, pagination, or any default behaviors. Given the tool's simplicity, this is fairly complete but not exhaustive.

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

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

Schema description coverage is 100%, so the baseline is 3. The description does not add meaning beyond what the schema already provides; it mentions 'period' but does not elaborate on the 'from'/'to' parameters or any date format specifics.

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 ('View') and resource ('your DAC usage report'), and further specifies the report's content ('breakdown of spending by service, period, and transaction type'). This clearly distinguishes it from siblings like get_dac_balance, which likely returns a simple balance rather than a detailed 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?

The description gives an implied use case ('Useful for budgeting and trajectory analysis') but does not explicitly state when to use this tool versus alternatives, nor does it mention conditions or exclusions. Some context is provided, but the guidance is not robust.

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 present, the description carries full responsibility for behavioral disclosure. It explicitly states the tool returns only the formal shape (enums, timestamps, hash) and never the content, which is a non-obvious and valuable constraint. It also enumerates the categories of information returned, giving a clear picture of the payload.

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

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

The description is compact at two sentences, with the primary action and scope in the first sentence and the return caveat in the second. There is no filler, and every clause earns its place.

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

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

For a simple retrieval tool with no output schema and no annotations, the description gives a solid picture of what is returned and explicitly constrains the response. It omits details like error behavior on a missing ID, but the essential context for calling correctly is present.

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

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

Schema description coverage is 100%, with both parameters (dd_id and auth_token) already well-documented in the input schema. The description adds no additional parameter-level meaning beyond echoing the ID concept, so the baseline score of 3 applies.

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

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

The description clearly states the verb 'Retrieve', the resource 'decision record', and the identifier method 'by its ID'. It also distinguishes this from siblings like list_decisions and get_decision_metadata_distribution by emphasizing a single record and specific return fields.

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 for fetching one specific decision when the ID is known, but it does not explicitly contrast it with siblings like list_decisions for enumeration or expose any when-not conditions. An agent can infer the use case, but there is no direct routing guidance.

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

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

With no annotations provided, the description carries the behavioral burden. It discloses the paid nature ('3 DAC') and the fact that the first call returns 402 with payment terms, which is valuable. However, it does not describe the success response format or any other behavioral consequences beyond the payment handshake.

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

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

The description is compact and front-loaded with the purpose, then immediately states the important payment constraint. The phrase 'returns 402 with payment terms first' is slightly awkward but the overall text is efficient and free of filler.

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

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

For a two-optional-parameter tool with no output schema and no annotations, this description is minimally adequate: it states the output dimensions, scope, and payment model. It does not explain the post-payment return shape or contrast with sibling distribution tools, but the schema covers the retry flow needed to invoke the tool correctly.

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

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

Schema description coverage is 100%, so the input schema already documents auth_token and payment_signature thoroughly. The description adds no new parameter-level meaning; its mention of decision_class and related terms refers to output content, not input parameters. 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 names the resource ('decision metadata distribution'), the exact breakdown dimensions ('decision_class, target_class, decision_trigger, human_involvement'), and the scope ('from your branch-1 decisions'). It stops short of explicitly distinguishing itself from the sibling get_self_classification_distribution, but the resource and fields are specific enough to avoid major confusion.

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 about when to use this tool versus alternative distribution/list tools among the siblings. The only usage-related information is the payment requirement and the 402-first behavior, which explains how to start calling it but not when it should be selected.

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 clearly indicates a read-only retrieval action ('Retrieve') and adds valuable context by listing the exact topics covered. It doesn't mention potential length or format, but for a simple documentation tool this is sufficient.

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?

One sentence with a structured comma-separated list. Every word adds value, and the colon-list format makes the coverage scan quickly. No redundant phrases.

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

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

For a parameterless, simple documentation tool with no output schema, the description fully conveys what will be returned and when to use it. It is complete without needing to explain return values or hazards.

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 need not explain parameters, and the schema already confirms there are none.

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 ('Retrieve') and resource ('the full agent guide for Decision Anchor'), clearly stating what the tool does. The enumerated topic list distinguishes it from the operational sibling tools, making its 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?

It explicitly instructs 'Read this before using DA,' providing clear timing guidance for when to invoke the tool. No alternatives need to be named since this is the primary documentation gatekeeper.

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 behavioral disclosure burden. It meaningfully discloses de-identification, k-anonymity (k>=10), and DAC cost. It doesn't fully describe return shape or authorization behavior, but the privacy and cost traits are valuable context.

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

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

Three short sentences, front-loaded with the core output and followed by essential privacy and cost caveats. Every sentence earns its place, with no filler or redundant schema 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?

With no output schema or annotations, the description provides the output concept and key constraints (de-identified, k-anonymous, cost), while the schema fully documents parameters including the payment challenge flow. It is adequate, though it could slightly strengthen agent confidence by naming when the payment challenge is triggered.

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

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

Schema description coverage is 100%, so the baseline is 3. The description's 'per dimension' phrase connects the dimension parameter to the output, but it adds no new parameter semantics beyond what the schema already documents for auth_token, period_days, and payment_signature.

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 clear verb ('Observe') and resource ('environment-level anomaly distribution'), and specifies the output ('within_band/outlier counts per dimension') plus a privacy constraint. It doesn't explicitly differentiate from sibling tools such as observe_environment or compare_anomaly, so it stops short of 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?

The description implies this tool is for examining population-level anomaly distribution and warns that it costs DAC, but it gives no explicit when-to-use guidance, exclusions, or alternatives. An agent must infer when to choose this over related observation/comparison 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 provided, the description carries the full burden of behavioral disclosure. It adds valuable context by stating that the tool costs DAC and outlining the report's contents. The 'get' verb implies a read-only operation, though it does not explicitly state that, and it does not mention any side effects beyond cost.

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, spanning two sentences with the primary purpose front-loaded. It packs in essential context (audience, content, cost) without waste, though a slight restructuring with line breaks could enhance 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 description adequately covers purpose, content, and cost for an external-audit report. It does not describe the return format, but it names the included components, and since there is no output schema, that is a minor gap. Payment mechanics are left to the parameter description, which 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 description coverage is 100% — all parameters (dd_id, auth_token, payment_signature) are documented in the input schema. The tool description adds no parameter-specific details beyond what the schema already provides, meeting the baseline for full 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 produces an external-audience evidence report for a decision, specifying the content (decision metadata, EE resolution, responsibility declaration) and purpose (external audit review). It distinguishes from siblings like get_decision by emphasizing the external-audience angle and cost, but it does not explicitly name an alternative, so it falls short of 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?

The description implies usage for external audit reports and notes that it costs DAC, which suggests using it only when such a report is needed. However, it gives no explicit guidance on when to choose this over alternatives like get_decision or get_documentation, nor does it state prerequisites or exclusions, leaving the when-to-use decision largely 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, the description carries the transparency burden. It conveys that the tool is free and that checking status is read-only in nature, but it does not explicitly state side-effect-free behavior or what happens when no ISE session exists. The description is adequate but not deeply revealing.

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 short sentences with no filler. The main purpose is front-loaded, and the second sentence adds actionable guidance about its relationship to exit_ise_session, making every word earn its place.

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

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

For a simple status-check tool with one optional parameter and no output schema, the description covers the essential information: what it checks, what fields it reports, its cost, and its relationship to a sibling tool. It does not describe the exact return shape, but the tool's simplicity makes this omission minor.

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 one optional auth_token parameter is already fully documented in the schema. The description adds no additional parameter meaning, which matches the baseline for high schema coverage.

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

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

The description clearly states the tool checks for an active ISE session and reports elapsed time and billing mode. It also explicitly connects to exit_ise_session, helping distinguish this tool from the related SDAC session 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 explicitly says to use this to find out what exit_ise_session will close, giving clear practical context for when to call it. It does not explicitly mention when not to use it or compare to get_sdac_session, but the use case is well 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 the full burden, and it does well: 'Look up' signals a read operation, 'Free' addresses cost, and the contrast with end_sdac_session clarifies this does not settle the session. It does not cover error cases or rate limits, but the key behavioral traits are disclosed.

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

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

Three short sentences, front-loaded with the core action and return fields, then value-add context about cost and relationship to end_sdac_session. No redundant filler; 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?

The description tells the agent what the tool returns, that it is free, and how it relates to session settlement. There is no output schema, so the description's mention of status, trial count, and accumulated cost is important. Minor gaps around missing-session behavior exist but are not critical for this simple lookup 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%: both auth_token and session_id are explained in the schema. The description only adds 'by ID,' which aligns with session_id but does not provide deeper parameter semantics 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 states a specific verb ('Look up'), a clear resource ('simulation session by ID'), and the exact data returned ('status, trial count, and accumulated cost'). It also distinguishes this tool from the related end_sdac_session by framing it as a preview of what that tool will settle.

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 explicit use context: 'Use this to see what end_sdac_session will settle,' and notes the tool is free, which helps an agent choose it over costlier operations. It does not explicitly list when not to use it or compare with other siblings like get_trial_status, but the guidance is present 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Observe' weakly implies a read-only operation, but the description does not explicitly state side effects, data freshness, auth requirements, or what form the distribution takes. The tool name already includes 'get', so the description adds little behavioral insight beyond a generic read intent.

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

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

A single, front-loaded sentence that contains no filler. Every word contributes to identifying the object and scope of the operation.

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, with one optional parameter and no output schema, so the description is close to sufficient. Still, with no annotations and no explanation of what 'branch-1 decisions' or the returned distribution looks like, an agent may need additional context to fully understand the result or the intended use case.

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

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

The only parameter, auth_token, is fully described in the schema with 100% coverage, including precedence behavior. The description adds no parameter-specific meaning, but it does not need to because the schema already documents the parameter adequately.

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 ('Observe') and resource ('self_classification distribution across your branch-1 decisions'), making the tool's purpose understandable. It does not explicitly differentiate from sibling tools like get_decision_metadata_distribution, so it misses full sibling distinction, but the scope is clear 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 implies when to use the tool: when you want to see your self_classification distribution over branch-1 decisions. However, it offers no explicit exclusions or alternatives, and it does not clarify how this differs from related distribution/observation 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 provided, the description carries the behavioral disclosure burden. 'Check' implies a read-only operation)Skip; but there is no explicit statement that it has no side effects, no mention of authentication behavior beyond the schema, and no description of edge cases such as an expired or inactive trial. The 500 DAC / 30 days context is useful plan information but not deep behavioral 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 short sentences, front-loaded with the core purpose, followed by relevant trial-plan context. No filler, no repetition of schema facts, and every clause contributes to understanding 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?

For a simple parameterless status tool, the description is largely complete: it states what information is returned and explains the trial allowances. There is no output schema, so the description appropriately sketches the return content. It does not mention what happens when a trial is expired or not yet active, but that is a moderate gap rather than a blocking one.

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

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

The schema has 100% description coverage for the single optional auth_token parameter, and the description adds no extra meaning to it. This aligns with the baseline of 3 for cases where the schema already documents parameters adequately.

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 ('Check') with a specific resource ('your trial account status') and enumerates what that includes: remaining DAC, days left, and usage so far. It is clearly distinguished from siblings like get_dac_balance or get_ise_status by the word 'trial', though it does not explicitly name or contrast any sibling.

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: whenever the agent needs to check trial account status. However, it provides no explicit guidance on when not to use it or how to choose among nearby alternatives such as get_dac_balance, get_ise_status, or run_sdac_trial. This leaves usage context implicit rather than stated.

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 discloses the scoping detail of the listing ('operator base + owner-registered'), but does not mention output format, ordering, pagination, or auth-related behavior. For a simple read/list operation this is acceptable but not rich.

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, both purposeful. The first states the core action and scope; the second provides actionable downstream context. No filler or redundancy.

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

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

For a low-complexity list tool with one optional parameter and no output schema, the description is sufficient: it names the resource, scopes the results, and explains why an agent would call it. It could add a bit more about the return shape, but the purpose is well covered.

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 single optional auth_token parameter is fully documented in the schema. The description adds no additional parameter-level meaning, which fits the baseline of 3 for high schema coverage.

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

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

The description clearly states the action ('List') and the specific resource ('available self_classification categories'), including the scope 'operator base + owner-registered'. It is distinct from the sibling get_self_classification_distribution by focusing on categories rather than statistics, though it does not explicitly name or contrast that sibling.

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 concrete downstream guidance: 'Use one of these keys in create_decision template.self_classification when content_inclusion_flag=1.' This tells the agent when the returned values are relevant, but it does not discuss alternatives or when not to use 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?

No annotations exist, so the description carries the full burden of behavioral disclosure. It only states that it lists records and shows trajectory, but does not mention read-only behavior, pagination semantics, date filtering effects, or what happens with no parameters. This is a gap for a list operation with five optional 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?

The description is very brief—two short sentences with no wasted words. The core action "List your decision records" is front-loaded, and the second sentence adds a small amount of contextual flavor without bloating the definition.

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 tool with no output schema, no annotations, and five optional parameters, the description is too thin. It does not explain what the response looks like, how the date range (from/to) works, whether ordering is applied, or how pagination is intended to be used. An agent would need to infer much of this from the schema alone.

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 all five parameters have individual descriptions in the schema. The description adds no additional parameter-level meaning, which is acceptable per the baseline of 3 when the schema fully documents parameters.

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

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

The description clearly states a specific verb and resource: "List your decision records." This distinguishes it from the sibling get_decision by implying a plural collection operation, and the added "trajectory" imagery reinforces the idea of reviewing history. It does not explicitly name alternatives, but the core action 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?

No guidance is provided about when to use this tool versus alternatives like get_decision or list_classifications. The phrase "See the trajectory you have built so far" mildly implies a review/history use case, but there are no explicit conditions, exclusions, or comparisons to 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 full burden. 'Browse' and 'Discover' imply read-only behavior, but it does not explicitly state that tools are safe/non-destructive or disclose any limitations (e.g., pagination). It adds minimal behavioral context beyond the core action.

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, front-loaded sentences with no redundant content. The first sentence states the primary action, and the second adds useful nuance about the marketplace's contents.

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 listing tool with a complete schema, the description is adequate but not comprehensive. It lacks mention of pagination behavior, authentication needs, or what the returned data looks like (no output schema). It is a minimally viable description.

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 all four parameters (page, layer, limit, status) already have descriptions in the schema. The tool description adds no additional parameter meaning, so the baseline score of 3 applies.

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

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

The description uses specific verbs ('browse', 'discover') and clearly identifies the resource ('agent-to-agent tool marketplace'), distinguishing it from siblings like register_tool and purchase_tool. It unambiguously communicates what the tool does.

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 alternatives like register_tool or purchase_tool. The description implies a browse-before-buy workflow but does not state preferred use cases 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states the cost (1 DAC), the authentication requirement (auth_token), the payment mechanism (x402), and the exclusion (Trial does not cover). This is significant behavioral context that helps the agent understand the side effects and prerequisites. It does not contradict any annotations.

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

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

The description is extremely concise at two sentences, with the core purpose front-loaded. Every word earns its place: the resource, the cost, the auth requirement, the payment method, and the trial exclusion. There is no filler or redundancy.

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

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

For a simple observation tool with two optional parameters and no output schema, the description covers the essential context: what it does, what it costs, what it requires, and what it excludes. The payment challenge flow is detailed in the schema, so the description need not repeat it. The only minor gap is that it doesn't specify the return format, but with no output schema and a simple statistics tool, 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 description coverage is 100%, so both parameters (auth_token and payment_signature) are already fully documented in the schema. The description adds no additional parameter-level meaning beyond what the schema provides, which meets the baseline of 3. It does not need to compensate for gaps.

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 'aggregate environment statistics' with specific metrics (active agents, total decisions, activity density). It distinguishes itself from other observe tools like observe_pattern by focusing on aggregate statistics, though it does not explicitly name an alternative. The purpose is specific and actionable.

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 context on when to use this tool by noting it costs 1 DAC and requires auth_token, and explicitly states Trial does not cover ARA observation. However, it does not mention when to prefer this over alternatives or when not to use it. The guidance is implicit rather than explicit about usage scenarios.

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 discloses the 1 DAC cost, the auth_token requirement, the x402 payment mechanism, the trial restriction, and even the version change (v1.3.1, formerly free). This is substantive behavioral context beyond what the schema provides. It does not contradict any annotations.

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

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

Two sentences, no filler. The purpose is front-loaded, and the cost/auth caveats follow. The sentence about the version change is slightly tangential but still informative. It earns its place by clarifying the tool's cost evolution.

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 tool with a payment flow, the description mentions cost and auth but relies on the schema for the challenge-response flow. There is no mention of return format or any side effects, though there is no output schema. Given the tool's moderate complexity and that the schema covers the payment mechanics, it is minimally adequate but could state what the response looks like or note that results are read-only.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds minimal semantic value beyond the schema: it mentions 'EE distributions' and 'action-type breakdowns' which loosely map to the type enum, but the schema already explains the enum values. The payment_signature flow is already detailed in the schema, so the description adds no extra 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?

The description states a specific verb ('Observe') and a concrete resource ('pattern-level EE distributions and action-type breakdowns across agents'). It clearly distinguishes from environment-level observation by specifying 'pattern-level', though it doesn't explicitly name sibling tools like observe_environment. 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 provides no guidance on when to use this tool versus alternatives. It does not mention that observe_environment might be for environment-level data, or when to choose ee-distribution vs action-type. Cost and auth requirements are stated, but they are prerequisites, not usage 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 provided, the description carries the full behavioral burden. It discloses meaningful behavior: creates a bilateral declaration and waits for counterparty acceptance, implying a blocking/synchronization aspect. However, it does not mention auth requirements, failure modes, timeouts, or what happens on rejection, leaving notable 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?

Three sentences, all informative and front-loaded: first the when, then the examples, then the exact mechanism. There is no filler, repetition of schema details, or unnecessary context.

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 explains the core purpose and high-level flow adequately, and the schema covers all parameter semantics. However, there is no output schema and the description does not describe the response format, timeout behavior, or how acceptance/rejection is surfaced, which is a meaningful gap for a complex 21-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 100%, so the parameters are already well documented and the description does not need to repeat them. The description adds context about the tool's purpose but no additional parameter-level meaning; the 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 states a specific action—propose a bilateral agreement to another agent—and explains the resource created (a DD with declaration_mode 'bilateral') and the behavior (waits for counterparty acceptance). It clearly differentiates this from single-agent decision tools like create_decision and confirm_decision by emphasizing the shared-boundary, both-must-agree context.

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 opens with explicit when-to-use guidance: 'Use when two agents need to fix a shared boundary' and gives concrete examples like payment splits and task delegation. It does not explicitly state when not to use it or name alternative tools, so it stops short of 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?

With no annotations provided, the description carries the burden of behavioral disclosure. It effectively discloses the payment mechanism (x402), the two-step challenge flow (via the schema but reinforced by the description), and the critical fact that Decision Anchor never holds the user's key or signs on their behalf. It does not detail error handling, rate limits, or post-purchase behavior, but the disclosures are substantial 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?

The description is succinct—two sentences that front-load the core purpose and then add key context about payment and trial exclusion. Every word adds value, with no redundancy or filler. It avoids unnecessary detail that belongs in the schema.

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 (payment, auth, idempotency), the description covers the essential usage context and points to the payment mechanism. The two-step payment flow is explained in the schema rather than the description, which is acceptable given 100% schema coverage. Still, a brief mention of the two-call flow in the description would have made it more complete for agents scanning quickly.

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%, meaning each parameter is well-documented in the schema. The tool description itself does not add extra semantic value beyond what the schema provides (e.g., it doesn't elaborate on auth_token or request_id). It relies on the schema's parameter descriptions, which aligns with the baseline of 3 for full 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 action ('Purchase a tool from the marketplace') with a specific verb and resource. It distinguishes itself from sibling tools like list_tools or get_agent_profile by focusing on the transactional purchase action. The mention of payment via x402 and trial exclusion further clarifies its unique role.

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 a clear usage context: this is the paid purchase route, and it explicitly notes that trial does not cover it, implying users on trial should seek alternatives. However, it does not name specific alternative tools (e.g., run_sdac_trial) or provide when-not-to-use cases beyond the trial exclusion, so it falls short of 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?

With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: decisions accumulate into an observable trajectory, which is important context. However, it doesn't disclose whether registration is idempotent, whether it has side effects beyond trajectory creation, or what happens if called multiple times. The description adds some value but leaves meaningful behavioral 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?

Two sentences with zero waste. The core action is front-loaded ('Register in this environment'), and the consequence is stated in one additional sentence. Every word earns its place.

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

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

For a single-parameter tool with no output schema, the description is mostly adequate. It explains the purpose and the key consequence (trajectory accumulation). However, it doesn't clarify whether registration is required before other tools, whether it can be called multiple times, or what the response indicates. These are minor gaps for a simple registration tool, but they prevent a higher score.

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

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

Schema description coverage is 100%, so the schema already fully documents the region_code parameter. The description adds no parameter-specific information beyond what the schema provides. Baseline 3 is appropriate since 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 clear verb and resource: 'Register in this environment.' It also adds a meaningful consequence ('Your decisions will accumulate into a trajectory that others can observe'), which distinguishes it from generic registration tools. However, it doesn't explicitly differentiate from sibling tools like register_tool, so it loses a point on sibling differentiation.

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: at the start of an environment session, before making decisions. It says 'Register in this environment' and explains the trajectory accumulation, which gives context. But it doesn't explicitly state when not to use it or mention alternatives (e.g., register_tool), so usage guidance is implied rather than explicit.

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

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

With no annotations, the description must disclose side effects, but it only states the outcome (publishing). It doesn't mention that this is a write operation, requires authentication, or has any cost or reversibility implications. The schema hints at auth_token, but the description omits it entirely.

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 concise sentence with no fluff, achieving maximum brevity. However, it lacks any structured detail, such as prerequisites or examples, making it lean but not fully informative.

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 tool with six parameters including a nested ara_connections array with enums and resolution levels, the description is far too sparse. It omits critical context about required connections, layer semantics, and output expectations, leaving the agent underinformed 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 description coverage is 100%, so all parameters are already documented. The description adds minimal extra meaning—only linking price_dac to revenue—but doesn't clarify other parameters like ara_connections or layer beyond schema text.

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 (publish) and the resource (a tool to the marketplace), making it immediately obvious what the tool does. It distinguishes itself from siblings like purchase_tool (buying) and register_agent (registering agents) by focusing on publishing 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?

No guidance is given on when to use this tool versus alternatives, nor are prerequisites mentioned (e.g., needing an existing tool or agent identity). The description only states the purpose without context for selection 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 are provided, so the description carries the full burden. It discloses key behaviors: it does not create a real record, it raises what end_sdac_session settles (trial_count x sdac_cost_ratio x base fee), and it is free to call. However, it does not detail side effects like rate limits or auth requirements beyond what is in the parameter schema.

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

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

The description is two sentences long with zero fluff. It front-loads the primary purpose (price a combination without creating a real record) and immediately adds the key behavioral note (free, affects session settlement). Very 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 tool with 9 parameters, 100% schema coverage, and no output schema, the description covers the critical context: simulation-only, cost-raising effect, and comparison to create_decision. It doesn't explain the return format (likely the DAC number), but given the schema richness and complexity, this 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?

Schema description coverage is 100%, so the baseline is 3. The description adds minimal parameter semantics beyond the schema, only implying that trial parameters affect the calculated DAC. Since the schema already documents each parameter, this is adequate.

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 verb (price) and resource (an EE combination inside a simulation session), and explicitly distinguishes it from create_decision by noting it returns the DAC cost without creating a real record. This helps an agent understand exactly what the tool does and how it differs from the sibling 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 implies when to use it (within a simulation session to estimate cost before creating) and mentions it is free to call, but does not explicitly state when not to use it or name an alternative (e.g., use create_decision when you want to actually create). Still, the comparison to create_decision and the simulation context provides clear guidance.

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

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

With no annotations, the description carries the burden. It discloses that the note is 'anonymous', that every field is optional, and that it's safe to skip any field. It does not disclose data persistence or limits, but the simplicity of the tool makes this sufficient.

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, concise sentence that front-loads the purpose ('Optional') and provides all necessary context without redundancy. Every word earns its place.

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

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

Given the tool's simplicity, no output schema, and full schema coverage, the description is complete. It tells the agent when to use it and that all fields are optional, which is all the agent needs to know.

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 covers all 8 parameters with descriptions, so baseline is 3. The description adds value by emphasizing that every field is optional and can be skipped, which is not explicitly stated in the schema (though implied). This clarifies that no parameter is required.

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 ('leave a brief, anonymous note') and the context ('if you've used this environment'). It is distinct from sibling tools like list_decisions or get_dac_balance, which serve different purposes.

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

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

Explicitly says 'Optional' and 'Not required to use anything here', and indicates when to use ('if you've used this environment'). It does not mention alternatives, but no sibling tool serves the same purpose, so no exclusions are needed.

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