decision-anchor-mcp
OfficialServer Quality Checklist
Latest release: v0.1.0
- Disambiguation3/5
Most tools have distinct purposes, but there are several overlapping observation/distribution tools (observe_environment, observe_pattern, get_environment_anomaly, get_decision_metadata_distribution, get_self_classification_distribution) and similar session lookup tools (get_sdac_session, get_ise_status) that could cause confusion. Descriptions help but boundaries are not always clear.
Naming Consistency4/5Tool names generally follow a verb_noun pattern with snake_case (create_decision, list_decisions, confirm_decision). There are minor deviations like 'propose_bilateral' (verb_adjective) and 'get_dac_ur' (abbreviation), but overall the naming is consistent and predictable.
Tool Count2/530 tools is heavy for a single MCP server, exceeding the typical range. While the breadth reflects the complex domain, several tools are highly specialized (e.g., multiple session types and distribution queries) and could be consolidated or split into separate servers.
Completeness3/5Core decision lifecycle (create, confirm, get, list) is present, along with simulation and analytics. However, there are notable gaps such as no explicit tool for accepting/rejecting bilateral agreements, no way to verify counterparty decisions, and no update/delete for self_classification or agent profile. These omissions may require workarounds.
Average 4/5 across 30 of 30 tools scored. Lowest: 3.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 21 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
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This repository includes a glama.json configuration file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the purpose without mentioning side effects, auth requirements, output format, or any operational nuances. For a read-only observation tool, it does not confirm that it is non-destructive or explain what happens when called.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the tool's purpose. Every word contributes meaning, with no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (1 parameter, no output schema) and the description is adequate for basic invocation. However, without an output schema, the description should indicate what the tool returns (e.g., a table, list, or summary). It does not, leaving the agent somewhat uncertain about the response format, so complete context is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the sole parameter (auth_token), so the schema fully documents it. The description adds no parameter-specific information, which is acceptable per the baseline of 3 when the schema covers everything.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Observe') and a specific resource ('your self_classification distribution') with a clear scope ('across your branch-1 decisions'). It is clear and distinct from the sibling tool get_decision_metadata_distribution, but it does not explicitly mention that alternative, so it lacks full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 like get_decision_metadata_distribution or get_agent_profile. There is no when-to-use or when-not-to-use context, leaving the agent to infer based solely on the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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.
Conciseness5/5Is 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.
Completeness3/5Given 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.
Parameters3/5Does 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.
Purpose5/5Does 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.
Usage Guidelines2/5Does 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.
- Behavior3/5
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 reveal a significant side effect: decisions will be accumulated into a trajectory that others can observe. However, it does not mention other behavioral traits such as whether registration is mandatory, if it can be undone, or any permissions or side effects beyond trajectory logging. This is partial transparency but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise: two short sentences that front-load the primary action ('Register in this environment') and add one valuable behavioral consequence. Every word serves a purpose, with no redundancy or filler. It is an excellent example of economy in tool descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool is simple (no required parameters, no output schema), the description is minimally sufficient, but it leaves some gaps. It does not explain the relationship to other tools like create_ise_session or create_decision, nor does it explicitly state that registration should occur before making decisions. The mention of a trajectory implies intended usage, but the description could be more complete for an agent to use it confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes both parameters (is_test and region_code) with 100% coverage, so the baseline is 3. The description adds no additional parameter-specific meaning beyond the schema; it only discusses the tool's overall purpose and effect. Since the schema handles parameter semantics adequately, this score is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool registers an agent in the environment, using the specific verb 'Register' and resource 'environment'. It explains a consequence (decisions accumulate into an observable trajectory), but it does not explicitly differentiate from the sibling tool 'register_tool' or other similar tools, though the name and wording strongly imply agent registration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description does not mention prerequisites, order of operations, or situations where it should not be used. It only states what registering does, so the agent is left without clear direction on when to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior itself. It mentions 'interactive sandbox session' and billing choices, but fails to disclose the session's side effects (e.g., whether it consumes resources, requires authorization, or returns a session ID). The operation is presumably a state-changing 'create', but no specifics are given about outcomes or prerequisites.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, each conveying essential information: what it does, why, and billing choice. No redundant text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description should compensate by explaining return values, side effects, and when it's appropriate. It only provides a minimal overview, leaving uncertainty about what the session creation entails and what the result is.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers both parameters with descriptions (100% coverage). The description adds context by mentioning 'Choose free, earned-only, or external billing' for the payment_mode parameter, which helps. However, it doesn't elaborate on the auth_token or the meaning of each billing mode beyond the schema's basic description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's function: 'Enter an interactive sandbox session' to 'Test decision strategies before committing real DAC.' This clearly identifies the tool as a sandbox session creator for testing, distinguishing it from real DAC operations. However, it doesn't explicitly differentiate from sibling tools like create_sdac_session, despite the sandbox context implying that distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear usage context: use this tool for testing decision strategies in a sandbox before committing real DAC. It implies this is the test environment vs real operations, but it doesn't explicitly exclude alternative tools or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden. It only says 'List' without disclosing that it requires authentication, supports date range filtering, pagination through limit/offset, or what the return format is. The read-only nature is inferred from the verb but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences that state the core function and intended use. No redundant information; front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for a basic list operation, but given five parameters including pagination and date ranges, it does not explain how the optional parameters affect results. It also does not distinguish from get_decision for single retrieval, which would help contextual placement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with descriptions for to, from, limit, offset, and auth_token. The description adds no information about these parameters or how they relate to the listing behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'your decision records', distinguishing it from get_decision which retrieves a single record. The added phrase 'See the trajectory you have built so far' reinforces the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for reviewing historical decisions, but it does not explicitly state when to use this tool versus alternatives like get_decision or get_decision_metadata_distribution. No exclusions or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of behavioral disclosure. It explains the revenue benefit but does not mention side effects, irreversibility, visibility of the listing, approval processes, or whether changes can be made later. This is a significant gap for a marketplace publishing operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the purpose and benefit. Every word earns its place, with no redundancy or extraneous detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and the tool's mutating nature (publishing to a marketplace), the description should provide more context about what happens after registration, such as listing visibility, confirmation responses, or potential errors. It currently only explains the benefit, leaving the agent without a full picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema descriptions cover all parameters (100% coverage), so the description adds no additional meaning. Baseline 3 applies because the schema does the heavy lifting; the description's mention of 'price in DAC' reinforces but does not extend the schema's clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Publish a tool you built') and the resource ('marketplace'), with a specific revenue angle that distinguishes it from sibling tools like purchase_tool or register_agent. It leaves no ambiguity about the tool's core function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: use this when you have built a tool and want to sell it in the marketplace. It doesn't explicitly exclude alternatives, but the sibling context and the description's specificity provide sufficient guidance. Slight deduction for not stating when not to use or mentioning prerequisite steps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose side effects. It mentions cost savings but does not explain session lifecycle, whether it creates persistent state, or how the session connects to run_sdac_trial/end_sdac_session. For a mutation-like create tool, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first states the core action; the second provides valuable rationale. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the description omits workflow context: it doesn't mention that a session will be used with subsequent SDAC tools or what the return value indicates. With no output schema, this missing guidance prevents it from being fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the single auth_token parameter with a description, so the baseline is 3. The description adds no additional parameter-specific meaning, but the schema already provides adequate coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Start a simulation session') and its purpose ('Test EE combinations at a fraction of the cost before creating real decisions'). This distinguishes it from sibling tools like get_sdac_session (retrieve) and create_decision (real action).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use it—before creating real decisions, as a cost-saving simulation. It implies an alternative (create_decision) but doesn't explicitly name or exclude other tools, so it's clear but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adds meaningful behavioral context: it is a read-only observation (implied by 'Observe'), de-identified with k-anonymity >= 10, and costs DAC. This provides transparency beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences clearly convey purpose, scope, privacy, and cost. There is no redundancy or filler, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core functionality, privacy guarantees, and cost. While it does not detail the exact response structure, the mention of 'counts per dimension' gives an adequate mental model absent an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description does not need to explain parameters. The tool description slightly augments the 'dimension' parameter by describing the output shape, but adds no critical semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Observe' with a clear resource: environment-level anomaly distribution, detailing the output as within_band/outlier counts per dimension across the population. This distinguishes it from decision-level or pattern-level tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 instead of alternatives like observe_environment or compare_anomaly. It mentions costs and k-anonymity, but does not provide usage context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
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 important behavioral traits: the 1 DAC cost, auth token requirement, version history, and trial limitations. However, it does not mention return format, side effects, or error behavior, so the disclosure is partial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each informative: purpose, cost/auth, and payment/trial info. It is front-loaded with the core functionality and contains no redundant phrases or excessive detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description lists what will be returned (active agents, decisions, density), which is helpful. It also covers cost, auth, and trial limitations. Missing specifics like response formatting or error handling, but for a simple observation tool this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already fully documents auth_token and payment_signature. The main description mentions 'requires auth_token' and 'paid via x402', but these do not add semantic meaning beyond what the schema provides, yielding the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool observes aggregate environment statistics, with specific examples (active agents, total decisions, activity density). This distinguishes it from sibling tools like observe_pattern or get_environment_anomaly by scope and subject, satisfying the 'specific verb+resource+scope' criterion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context about cost and auth token requirements but does not explicitly state when to use this tool versus alternatives or mention any exclusionary criteria. The usage is implied (observe environment stats), but no direct contrast with sibling tools is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses the payment mechanism (x402), the side effect (creator earns DAC), and trial exclusion. However, it omits the two-step payment challenge flow, which is only detailed in the parameter description, so it is not fully transparent on its own.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: two sentences that cover purpose, payment, and trial exclusion without wasted words. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity and the rich schema that fully documents all four parameters, the description provides sufficient context for an agent to understand the tool's role. It does not explain the return value, but with no output schema and the schema covering the core workflow, the description is adequate though not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-level meaning, but the schema already provides thorough documentation, especially for payment_signature with its detailed explanation of the x402 challenge flow.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Purchase a tool') and resource ('from the marketplace'), with a specific and unique purpose. It also distinguishes itself from trial tools by noting 'Trial does not cover this route,' which differentiates it from sibling trial-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: it is for purchasing tools, not for trial access. It explicitly mentions what is not covered ('Trial does not cover this route'), but does not name alternative tools or provide explicit when-to-use vs. when-not-to-use guidance beyond that.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavior. It adds useful context about the 409 conflict with create_ise_session. However, 'settle it' is vague and it doesn't mention side effects, idempotency, or what the tool returns.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, front-loaded with the core action, and every word contributes value (including the useful 409 caveat). No wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no output schema and no annotations, the description covers the primary purpose and a key behavioral consequence. However, it leaves 'settle it' undefined and doesn't explain return values, which is a notable gap given the absence of an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% — both auth_token and payment_signature have detailed descriptions in the schema. The tool description adds no additional parameter meaning, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('End') and the resource ('active interactive sandbox session'). It differentiates from sibling tools like create_ise_session and end_sdac_session by specifying that it's for ISE sessions, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to call it 'when you are done' and provides a concrete consequence of not calling it (create_ise_session returns 409 SESSION_EXISTS). While it doesn't name alternative tools, the context makes usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It does disclose that the tool 'Costs DAC,' which is a key constraint. However, it omits other behavioral details such as potential side effects, failure modes, or the two-step payment challenge flow (the latter is only covered in the schema's payment_signature parameter).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded, using two sentences to convey purpose, content, and cost. There is no redundant information, and every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description should specify the return format or clarify what the agent receives. It lists report contents but omits response structure and prerequisites (e.g., existence of the decision). Core purpose and cost are covered, but completeness is moderate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for all three parameters (auth_token, dd_id, payment_signature). The description adds no additional meaning to the parameters, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: generating an external-audience evidence report for a decision, and lists included components (decision metadata, EE resolution, responsibility declaration). This distinguishes it from sibling retrieval tools like get_decision by emphasizing report generation for external audit review.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when an external-audience evidence report is needed) and provides context about the report's structure. However, it does not explicitly mention alternatives or when not to use it, so it lacks the exclusions that would earn a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must convey behavioral traits. It discloses the payment mechanism and trial limitation, which is useful. But it does not describe side effects, permissions beyond the auth token, or response behavior beyond the listed contents, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, first states purpose, second adds payment caveat. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 params, no output schema), the description covers purpose and key usage caveats. It lists output components, which helps set expectations, though no explicit return format is given. Adequate for the complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions, including the payment_signature flow. The tool description does not add further meaning beyond schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's function with a specific verb 'View' and resource 'an agent's decision profile', listing concrete components (trajectory shape, EE patterns, activity summary). It also differentiates via ARA observation and payment model, distinguishing it from sibling tools that focus on decisions or sessions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context about payment requirements (x402, trial not covering it), which indicates when this tool is necessary. However, it does not explicitly name alternatives or exclusion scenarios compared to sibling tools, so it stops short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the transparency burden. The verb 'View' clearly indicates a read-only operation, and the description mentions the breakdown content. However, it does not explicitly state that the tool performs no mutations, nor does it disclose any required permissions or side effects, leaving room for more clarity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two sentences that immediately state the tool's purpose and use case. It front-loads the key information and avoids fluff or redundancy. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only report tool with a simple parameter set, the description is complete enough. It explains what the report contains and why it is useful. The absence of an output schema is mitigated by the description's explicit mention of 'detailed breakdown by service, period, and transaction type.' It could have mentioned required auth explicitly, but the schema covers that, so overall this is well-rounded.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% description coverage for all three parameters (to, from, auth_token), so the baseline is 3. The description adds no extra semantic detail beyond alluding to a 'period' via the date parameters, but since the schema is thorough, this is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'View your DAC usage report — a detailed breakdown of spending by service, period, and transaction type.' It uses a specific verb ('View') with a specific resource ('DAC usage report') and distinguishes it from related tools like get_dac_balance by emphasizing the detailed breakdown and spending analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: 'Useful for budgeting and trajectory analysis.' It implies this is the go-to tool for viewing spending reports but does not explicitly mention alternative tools or exclusion criteria, 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.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the operation is free and lists returned fields, but it doesn't explicitly state it's read-only or discuss any side effects or permissions beyond the auth_token parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two compact sentences, front-loads the purpose, and includes the helpful 'Free' detail without wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool, the description adequately covers what, when, and cost. It doesn't detail the response structure, but no output schema exists and the listed return fields suffice.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both params, so the baseline is 3. The description adds minimal parameter insight beyond identifying session_id as the lookup key.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action (look up), the resource (simulation session by ID), and specifies the returned data (status, trial count, accumulated cost), which distinguishes it from other session/trial tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear use case ('Use this to see what end_sdac_session will settle') and notes it is free, but it doesn't explicitly contrast with alternatives like get_trial_status or run_sdac_trial.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It discloses that the list includes operator base and owner-registered categories, which is useful context. However, it does not state whether the operation is read-only, whether special permissions are needed, or describe any side effects, though the name 'list' implies a safe read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: one for purpose and one for usage. Every word earns its place; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with one parameter and no output schema, the description tells what it returns (keys) and how to use them. It doesn't detail the response structure or potential error conditions, but it is sufficient for a basic list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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. The description adds no extra parameter-specific details, but schema coverage is 100%, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists available self_classification categories, specifying the scope (operator base + owner-registered). It distinguishes from siblings like get_self_classification_distribution by focusing on listing categories rather than distributions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent when to use this tool: to obtain keys for use in create_decision's template.self_classification when content_inclusion_flag=1. It does not mention alternatives or exclusions, but the use case is clearly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the return fields (remaining DAC, days left, usage) but does not explicitly state whether the operation is read-only or if there are side effects. The implied nature of a 'status check' is helpful but not fully explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main purpose and immediate detail. Every word earns its place; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description adequately covers what the tool does, what it returns, and relevant context (trial limit). It is complete for an agent to decide when and how to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the single parameter (auth_token) with a clear description. The tool description adds no additional parameter semantics, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Check your trial account status' and lists specific details (remaining DAC, days left, usage). This clearly distinguishes it from siblings like get_dac_balance and get_ise_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the trial context (500 DAC for 30 days) and implicitly suggests this tool for trial-related status checks. It does not explicitly mention alternatives or exclusions, but the context makes the use case clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool returns band_position values across 5 dimensions and that it costs DAC, which are behavioral traits not present in the schema. It does not detail the payment challenge flow, but that is covered in the payment_signature parameter description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that immediately state the purpose, output, and cost, with no redundant or unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description, combined with the fully descriptive schema, gives enough information to invoke the tool: it specifies the input (decision ID), optional window, and the expected output format. The absence of an output schema is mitigated by the clear description of the return value. Some details like payment challenge are in the param description, making the overall definition complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All four parameters have descriptions in the schema, and the schema coverage is 100%. The main description does not add additional parameter semantics beyond what the schema already provides, but it does not need to.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Compare') and resource ('your decisions against your accumulated pattern'), and specifies the exact output dimensions. This clearly distinguishes it from sibling tools like observe_pattern or get_environment_anomaly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states the tool is used to compare a decision to the accumulated pattern, implying it's appropriate when you have a decision ID and need an anomaly classification. It does not explicitly mention alternatives or exclusions, but the context is clear enough for an agent to select it over similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description conveys the operation is a check/read action, implying no side effects. It adds detail about the two balance types. It does not explicitly state security or error behavior, but for a simple balance check, this 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action and immediately clarifies the two balance types. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with a single parameter and no output schema. The description conveys what will be returned (balance types) and when to use it, making it sufficiently complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully documents the only parameter (auth_token), and the description does not add additional parameter information. Baseline of 3 applies since schema coverage is 100%.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks the user's DAC balance, differentiating between External (funded) and Earned (from tool sales). This is specific and distinct from sibling tools like get_dac_ur or get_agent_profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context for when to use the tool ('Know what you have before you decide what to spend'), implying it should be used prior to spending actions. However, it doesn't explicitly mention alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 reveals a critical trait: 'never its content', indicating the tool excludes substantive content and only returns formal metadata (enums, timestamps, hash). It also mentions lineage and scope, which adds context beyond the schema. However, it does not discuss error behavior or permission requirements beyond the auth_token parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the verb and resource. It avoids redundant phrasing, precisely states the return scope, and includes a critical negative constraint ('never its content') without unnecessary words. Every sentence contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, no output schema), the description sufficiently explains what is returned: declared fields, scope, lineage, and formal shape. Without an output schema, it provides a clear high-level view of the return structure. It could mention error cases (e.g., not found) but this is not critical for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage for the two parameters (dd_id and auth_token), each with a clear description. The tool description adds no new meaning about parameter usage or syntax; it only implies dd_id via 'by its ID'. Since schema coverage is high, the description's lack of additional parameter detail is acceptable, and the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a specific decision record by its ID, with an explicit verb ('Retrieve') and resource ('decision record'). It further specifies what is returned (declared info, scope, lineage) and distinguishes itself by emphasizing it returns only the formal shape, never content, which separates it from siblings like get_decision_metadata_distribution or list_decisions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: use this when you need a single decision's formal structure by ID. The 'never its content' clause implies a limitation but does not explicitly name alternative tools (e.g., 'use get_decision_metadata_distribution for aggregates'). Thus it provides clear context without explicit exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 tool costs DAC and uses 'Observe' to imply a safe, read-only operation. However, it does not detail return structure, pagination, or rate limits, so it provides only partial 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the purpose, specifies the fields, and includes the cost caveat. Every word earns its place with zero fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with one parameter and no output schema, the description is largely complete: it states the fields, scope (branch-1 decisions), and cost. It lacks details about response formatting or edge cases, but these are not critical for understanding the tool's core function.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (auth_token described. The description adds no additional parameter semantics beyond the schema, which is fully self-explanatory. Baseline of 3 is appropriate because the schema carries all parameter information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Observe' to indicate viewing, identifies the resource as 'decision metadata distribution', and lists the exact fields broken down (decision_class, target_class, decision_trigger, human_involvement). It distinguishes from the sibling get_self_classification_distribution by scoping to 'branch-1 decisions'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use this tool to see a breakdown of decision metadata from branch-1 decisions. It does not explicitly name alternatives or exclusions, but the scope is well-defined. Mentioning 'Costs DAC' adds important usage guidance about the tool's cost.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool is a read-only check ('Check'), is free, and provides session details (elapsed time, billing mode). It does not describe return format or potential side effects, but for a status query, the essentials are covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the primary purpose and immediately followed by a practical note. Every word earns its place, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple status-check tool with one parameter and no output schema, the description covers purpose, cost, and a related use case. It lacks detail on the exact output structure, but that is not critical for such a straightforward operation given the limited complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the single parameter (auth_token) with 100% coverage. The description does not add additional parameter-specific context, which is fine given the schema's clarity. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: checking for an active interactive sandbox session, along with elapsed time and billing mode. It also distinguishes itself from sibling tools by noting it reveals what exit_ise_session will close, making the resource and scope explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides a specific use case ('Use this to find out what exit_ise_session will close') and notes the tool is free, which helps with cost/utility decisions. However, it does not explicitly mention when not to use this tool or compare it with other session-related tools like get_sdac_session.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility. It discloses key behavioral traits: the created DD has declaration_mode 'bilateral', the tool 'waits for counterparty acceptance', and anchoring only happens after mutual agreement. This is meaningful, though it omits rejection handling or timeout behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the 'Use when' directive, and each clause adds value. No filler, repetition, or irrelevant detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is complex with 21 parameters, but the schema is exhaustive. The description explains the core proposal-and-acceptance flow and use cases. It does not describe the return value (though no output schema exists), which is a minor gap for such a feature-rich tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all 21 parameters documented via types, enums, and defaults. The description's mention of declaration_mode 'bilateral' provides conceptual context but does not enhance parameter-level understanding 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'propose' with a clear resource ('a bilateral agreement to another agent'). It explicitly distinguishes from sibling tools by stating it creates a DD with declaration_mode 'bilateral' and waits for counterparty acceptance, unlike unilateral creation tools. Use cases like payment splits and task delegation clarify scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The opening phrase 'Use when two agents need to fix a shared boundary' provides explicit when-to-use context, reinforced by concrete examples. However, it does not explicitly state when NOT to use this tool or name alternative tools, so it stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that no real record is created, that the call is free in the immediate sense, and that each trial raises the final settlement via a specific formula. This goes beyond basic mutation behavior and helps the agent understand side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and the second sentence efficiently adds cost implications and side effects. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description clearly states the return value (DAC cost) and the side effect on end_sdac_session settlement. It does not explain the session lifecycle in depth, but the schema covers the session_id parameter and the sibling tools imply the workflow. This is sufficiently complete for a tool with a 100%-covered schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and each parameter already has a description. The description introduces the term 'EE combination' which groups several parameters but adds no new syntax or format details 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Price') and resource ('EE combination'), clearly scopes it to a simulation session, and explicitly contrasts with create_decision by stating it does not create a real record. This strongly distinguishes it from sibling tools like create_decision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'without creating a real record' and the reference to 'same combination would cost on create_decision' imply this tool is for pricing without committing. However, it lacks explicit when/when-not guidance or prerequisites beyond the session ID requirement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the tool is anonymous and that all fields are optional, which are useful behavioral traits beyond the schema. However, it does not describe what happens after submission, but for a low-risk feedback 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences long, front-loaded with the key word 'Optional,' and every phrase adds value. There is no redundancy or filler, making it highly concise and well structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple feedback tool with no output schema and all-optional parameters, the description is complete. It explains what the tool does, when to use it, and that nothing is required. No important context is missing for the agent to decide whether to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with each of the 8 parameters clearly described as optional. The description adds only that every field is optional, which is redundant with the schema. This meets the baseline of 3 for full schema coverage, but doesn't add extra meaning beyond that.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to leave a brief anonymous note about the user's experience. It uses a specific verb ('leave') and resource ('note'), and is distinct from all sibling tools, which are about environment, decisions, or agents, not feedback.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says the tool is optional and for those who have used the environment, providing clear context. There are no alternative feedback tools among siblings, and it does not explicitly say when not to use it, but the optional nature is well communicated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It discloses key behavioral traits: confirmation fixes the scope externally, and the integrity hash/timestamp are created at declaration time, not at confirmation. It does not cover idempotency or error conditions, but adds substantial context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each adding necessary information: workflow position, effect, parameter requirement, and timing. No filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter confirm tool with no output schema, the description covers the workflow, timing, effect, and parameter requirement well. It lacks details on response format or idempotency, but such information is likely not critical for this operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, giving a baseline of 3. The description adds meaning by explicitly stating that only dd_id is needed for the action, clarifying the role of the parameter and the irrelevance of hash/timestamp at this step.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Confirm a pending decision — marks the anchored declaration as settled.' It also distinguishes from siblings by explicitly referencing create_decision and noting that confirm requires only the dd_id, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage timing: 'Use after create_decision' and 'Call this after the action described in the DD has been executed.' It implies not to use before those steps, though it does not explicitly mention alternative tools for other scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 reveals the session lifecycle (the 409 until closed) and implies a financial settlement, but does not explicitly state irreversibility or that it is a mutating action. The payment-signature flow is explained in the schema, not the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences: the first states the purpose, the second gives usage guidance. No redundant or filler content; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, usage timing, and a key behavioral consequence. Without an output schema, it would benefit from stating what the response contains (e.g., final cost or confirmation), but this is a minor gap given the tool's simplicity and the already-rich schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add parameter-specific meaning beyond the schema; it references session_id implicitly via 'session' but does not elaborate on any parameter. The schema descriptions are already detailed, especially for payment_signature.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('End a simulation session and settle its accumulated cost') with a clear resource and effect. It distinguishes from the sibling create_sdac_session by explicitly noting the 409 conflict until the session is closed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It says 'Call this when you are done' and explains the consequence of not doing so (create_sdac_session returns 409 SESSION_EXISTS). This provides clear when-to-use guidance and implies the alternative (creating a new session) is blocked until this is called.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden and does exceptionally well: it discloses cost (1 DAC), auth requirement, payment flow via x402 (including the challenge-response mechanism), and trial exclusion. It also notes version history ('formerly free'), providing valuable operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and densely packed with relevant information: what it does, what data it returns, cost, auth, and payment specifics. Every phrase earns its place, and the structure is front-loaded with purpose before operational details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description explains the return data (EE distributions, action-type breakdowns) and the payment flow sufficiently. It could be more explicit about response format or pagination, but the core behavior is clear. The 'across agents' scope is somewhat ambiguous but acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 little beyond the schema: it re-emphasizes the auth_token requirement and mentions payment_signature in passing, but these are already described in the schema. No additional parameter-level insights are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Observe' with a clear resource ('pattern-level analytics') and specifies the data types ('EE distributions and action-type breakdowns across agents'). This directly distinguishes it from sibling tools like observe_environment, which likely focuses on environment-level observations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states the tool's purpose and adds crucial context about cost and authorization, implying when it should be used (when you need pattern analytics and can pay). However, it does not explicitly mention alternatives or when not to use it, so it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does so thoroughly: it discloses tamper-evidence, the record trajectory, external checking against DA, the EE-axis defaults with current DAC totals, preset adjustability, and automatic trial application. These are meaningful behavioral facts that go beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, front-loaded with the primary use case, then efficiently delivers pricing and default behavior details. Every sentence earns its place; there is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex 25-parameter mutation tool with no output schema, the description provides solid invocation context, defaults, and cost information. However, it does not explain the response/confirmation flow or how this tool fits into later sibling operations like confirm_decision, leaving some contextual gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% parameter coverage with detailed descriptions, so the baseline is 3. The description adds genuine value by explaining the EE axes/presets, cost implications of omitting axes, and branch behavior, enriching the semantics without re-listing all 25 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Use when your agent is about to execute an action that crosses an external boundary — payment, delegation, or agreement with another agent' and then says 'Record a tamper-evident decision.' This clearly states the verb, resource, and invocation context, distinguishing it from siblings like confirm_decision and propose_bilateral by emphasizing the pre-execution recording function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives an explicit 'Use when' condition for boundary-crossing actions and notes 'before execution.' However, it does not name alternatives or state when not to use the tool, leaving the distinction from related sibling tools implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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.
Conciseness5/5Is 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.
Completeness5/5Given 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.
Parameters4/5Does 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.
Purpose5/5Does 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.
Usage Guidelines5/5Does 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.
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