neurogenesis

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the ranking mechanism ('by learned edge weight and trust') but omits crucial information such as side effects (none expected), error behavior (e.g., invalid node), authorization requirements, or rate limits. More details about the algorithm's assumptions or limitations would improve transparency.

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

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

The description is a single sentence, making it concise. However, it is somewhat dense and could be structured with more clarity (e.g., breaking into purpose and key details). It effectively front-loads the purpose but sacrifices comprehensiveness for brevity.

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

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

Given the tool's complexity (3 parameters, no annotations, but an output schema exists), the description is too minimal. It does not explain how to use the tool in context, potential use cases, or what the output represents. With an output schema present, descriptions of return values are less critical, but the description still fails to provide enough operational context.

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

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

The parameter schema coverage is 0%, meaning the description does not explain any parameter. The schema defines 'agent_id', 'from_node', and 'limit', but the description only alludes to 'from_node' indirectly ('from a given node'). It does not clarify the role of 'agent_id' or the default value and meaning of 'limit'. Without this, agents cannot infer correct usage.

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

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

The description clearly states the tool's purpose: recommending the strongest next cognitive steps from a given node based on edge weight and trust. It uses specific terms like 'routing recommendation' and 'cognitive steps', making it distinguishable from siblings like 'route_task' which likely handles task routing. However, it could be more explicit about what constitutes a 'node'.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, expected inputs, or when not to use it. The sibling tools list includes similar-sounding tools like 'route_task' and 'compute_efficiency_report', but no differentiation is offered.

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

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

With no annotations provided, the description carries the behavioral burden. It explicitly declares 'Free read' signaling a side-effect-free operation, and adds a meaningful guarantee: 'Estimates and observations stay distinct.' This goes beyond a simple read-only label and clarifies data handling. However, it does not mention any potential limitations like data freshness or computational cost, so it's not a 5.

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

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

The description is a single sentence with a colon-led list, front-loading 'Free read' for immediate clarity. While the list is long, each item adds specific content scope. It's efficient and well-structured, though slightly dense.

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

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

An output schema exists, covering return structure, so the description needn't explain return values. It does provide a comprehensive list of report contents and a behavioral guarantee. However, it omits any mention of the 'limit' parameter and doesn't explain how the report relates to sibling tools like route_task or record_route_outcome, making it less complete for an agent deciding when to invoke it.

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

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

The input schema has one parameter 'limit' with a default value but no description. Schema description coverage is 0%, so the description should compensate, but it never mentions 'limit' or how it affects the report. The parameter's meaning is left entirely to inference from its name and type, which is insufficient.

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

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

The description uses a specific verb 'Free read' followed by a detailed resource list: decision/outcome receipts, route modes, compute avoided, predicted savings, predicted-vs-observed cost/latency/energy coverage, and Landauer-floor context. This clearly distinguishes it from sibling tools like get_ledger or list_agents by specifying exactly what efficiency metrics are reported.

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

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

No explicit guidance on when to use this tool versus siblings. It doesn't state 'use this to retrieve efficiency metrics' or mention alternatives like get_ledger for raw data. The usage is only implied by the name and description, but the description lacks direct when-to-use/when-not-to-use instructions.

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

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

With no annotations, the description carries full burden but only mentions creation and return values. It does not disclose side effects, authentication needs, or idempotency, leaving behavioral aspects unclear.

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

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

The description is concise and front-loaded with the action, but the template format could be more structured (e.g., bullet points). Slightly above average.

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

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

Given the complexity and presence of an output schema, the description covers the key inputs and outputs. It omits error handling and validation details but is adequate for a creation tool.

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

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

The schema has 0% coverage and the genome property is an open object. The description compensates by specifying required fields (agent_name, purpose, initial_nodes, fitness_metrics) and optional fields (growth_rules, safety_axioms) with constraints like uniqueness and minimum count.

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

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

The description clearly states the tool creates a developmental agent from a digital genome, and lists required and optional fields. It is distinct from sibling tools like delete_agent or describe_agent.

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

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

No guidance is provided on when to use this tool versus alternatives, such as import_state or other creation methods. The description lacks usage context.

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

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

With no annotations, the description must disclose behavioral traits. 'Remove' implies deletion but does not explain irreversibility, effect on related data, or required permissions. The lack of detail could lead to misuse.

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

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

The description is a single, concise sentence with no unnecessary words. It earns its place without verbosity.

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

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

Despite the presence of an output schema and moderate complexity, the description fails to provide enough context about the 'mount' concept, agent lifecycle, or return value. The single sentence is insufficient for confident tool use.

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

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

Schema coverage is 0%, so the description should compensate by explaining parameters. It does not: agent_id and request_id are not described at all. The schema already lists types but the description adds no value.

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

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

The description clearly states the action (Remove) and resource (developmental agent), distinguishing it from sibling tools like create_agent or get_agent. The phrase 'from this mount' is slightly vague but contextually understandable.

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

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

No guidance on when to use this tool versus alternatives such as deactivating or archiving an agent. No prerequisites or post-conditions mentioned.

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

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

With no annotations provided, the description carries the full burden. It mentions returning capabilities and input contract, but does not disclose whether this is a read-only operation, requires authentication, or has any side effects. For an introspection tool, safety is likely but not stated.

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

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

The description is extremely short (5 words), which is concise but sacrifices clarity. It could benefit from being more descriptive while still remaining succinct. It is not overly verbose but borders on under-specification.

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

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

Given that there is an output schema (not shown), the description does not hint at what the return value contains beyond 'capabilities and input contract'. For a simple introspection tool, more detail about the structure or content of the output would improve completeness.

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

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

The input schema has zero parameters and 100% coverage, so the description does not need to explain parameters. However, it adds no value beyond the schema; it repeats the obvious purpose. Baseline 3 is appropriate.

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

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

The description 'Return capabilities and input contract' gives a general sense of introspection but doesn't specify what agent it describes or how it differs from siblings like get_agent (likely returns agent details) or list_agents (lists all agents). It is moderately clear but would benefit from more specificity.

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

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

No usage context is provided. There is no indication of when to use describe_agent versus siblings such as get_agent or compute_efficiency_report. The description lacks any guidance on prerequisites or alternatives.

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

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

With no annotations, the description should disclose behavioral traits. It mentions portability and recreation anywhere, but lacks details on side effects, permissions, or output format.

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

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

The description is a single sentence that is front-loaded and concise. It efficiently communicates the core function, though it sacrifices detail.

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

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

Given the tool has one parameter and an output schema, the description partially covers the function and output portability. However, it lacks completeness by not explaining what the state document contains.

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

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

Schema coverage is 0%, yet the description provides no information about the agent_id parameter. The agent needs to infer its meaning from context, which is insufficient.

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

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

The description clearly states the tool creates a 'portable state document' for an agent and mentions import_state as counterpart, indicating export. However, it could be more explicit with an action verb like 'Exports'.

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

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

The description only implies usage by mentioning import_state. It does not provide guidance on when to use this tool versus alternatives like get_agent or describe_agent, nor does it specify prerequisites.

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

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

With no annotations, the description carries full burden. It discloses that the tool returns genome, cognitive graph, and summary counts, which implies read-only behavior. However, it does not mention potential performance impact (e.g., large graph size) or any constraints like recency of state.

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

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

The description is a single sentence that front-loads 'Full current state' and lists key components. It is concise with no redundant information, though listing items in bullet form could improve skimmability.

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

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

Given the complexity of the state and the presence of an output schema (not shown), the description provides adequate high-level coverage of return content. However, it lacks details on error handling, such as behavior when agent_id does not exist, and does not contrast with the similar describe_agent sibling.

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

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

Schema description coverage is 0%, so the description must compensate for parameter meaning. The description does not mention the agent_id parameter at all, leaving the agent to rely on the parameter name alone. Although agent_id is self-explanatory, the description should explicitly state it is required and perhaps advise on format or source.

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

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

The description clearly states that the tool returns the full current state including genome, cognitive graph with nodes/edges/weights/trust, and summary counts. This distinguishes it from sibling tools like describe_agent (likely a summary) and export_state (for serialization).

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

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

No guidance on when to use this vs alternatives. There is no mention of when to prefer get_agent over describe_agent, export_state, or list_agents. An agent may need to infer usage from context.

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

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

No annotations are present, so the description must disclose behavior. It hints at read-only via 'append-only' but does not mention important details like pagination, performance, or that events are returned as-is (verbatim).

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

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

The description is very short, which is concise, but the phrasing is somewhat cryptic (e.g., 'NG3 — returned verbatim') and lacks clear structure. It could be more straightforward.

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

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

The tool has an output schema, which mitigates the need to describe return values. However, the description does not cover the context of the ledger (e.g., ordering, filtering) or how parameters affect results.

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

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

Schema description coverage is 0%, and the description provides no explanation of the 'agent_id' or 'limit' parameters. The agent must rely solely on parameter names and types to infer meaning.

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

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

The description explains the ledger's content (growth, pruning, evaluation events with reasons) but does not use an explicit verb like 'retrieve' or 'get'. The action is implied by the tool name, making the purpose somewhat vague.

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

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

No guidance is provided on when to use this tool versus siblings (e.g., get_agent, list_agents). The description only states what the ledger is, not when it should be accessed.

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

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

The description implies a write operation but does not disclose side effects (e.g., overwriting existing agents), permissions needed, or error scenarios. Since no annotations are provided, the description carries full burden and fails to provide sufficient behavioral context.

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

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

The description is a single sentence, which is concise, but it omits necessary details, making it too sparse. It could be expanded without losing conciseness.

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

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

Given the tool's moderate complexity (nested object, output schema exists), the description is incomplete. It lacks behavioral transparency, parameter details, and usage context. The existence of an output schema does not compensate for missing entry-level guidance.

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

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

Schema description coverage is 0%, yet the description adds no information about the parameters. It hints that 'state' is an export state document but gives no format or structure details. The optional 'request_id' parameter is not mentioned at all.

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

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

The description clearly states the action ('Recreate an agent') and the resource ('from an export_state document'). It distinguishes from sibling tools like 'export_state' (inverse) and 'create_agent' (different source).

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

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

No guidance on when to use this tool vs alternatives. It does not specify prerequisites, such as having a valid export_state document, or exclusions (e.g., not for creating agents from scratch).

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

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

No annotations are provided, so the description carries full burden. It discloses that the tool lists all agents and provides summary counts, implying a read-only operation. However, it does not mention authentication needs, pagination, or response format beyond counts. Adequate but could be more detailed.

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

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

The description is a single, concise sentence that is front-loaded and contains no redundant information. Every word earns its place.

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

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

Despite having no parameters and an output schema, the description is somewhat cryptic with phrases like 'developmental agents' and 'on this mount'. It does not explain what 'developmental' means or clarify the scope. Additional context would improve completeness.

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

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

The input schema has no parameters (0 parameters, 100% coverage). The description adds no parameter information, which is appropriate. Baseline for zero parameters is 4.

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

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

The description clearly states the tool lists all developmental agents with summary counts, using verb 'list' and specifying the resource 'developmental agents' and scope 'on this mount'. However, the term 'developmental' may be ambiguous without further context. It distinguishes from siblings like get_agent (single) and create_agent.

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

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

No guidance is provided on when to use this tool versus alternatives like get_agent or describe_agent. The description does not mention use cases, limitations, or exclusions.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It transparently states that optional metrics 'remain explicitly unknown when omitted' and that outcomes are 'append-only, hash-bound,' revealing immutability and integrity properties. It does not mention authentication or rate limits, but the core behavior is well disclosed.

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

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

The description is three sentences long, front-loaded with the action, and every sentence provides substantive information: the action, the optionality semantics, and the constraint. There is no filler or repetition.

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

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

Given an output schema exists and the tool is a simple append operation, the description covers the essential context: purpose, optional fields, and immutability. It lacks explicit mention of how to obtain a 'Wu Wei decision' or any prerequisites, but the sibling tool 'route_task' likely provides such context. Overall, it is nearly complete for the tool's complexity.

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

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

The description adds meaning beyond the schema by clarifying that 'Actual cost, latency, and energy are optional and remain explicitly unknown when omitted,' giving semantic weight to null defaults. However, it does not elaborate on decision_id, success_score, notes, or request_id, leaving those to schema-only understanding. With 0% schema coverage, the description partially compensates but is incomplete for all parameters.

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

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

The description's first sentence, 'Attach one observed outcome to a Wu Wei decision,' uses a specific verb and resource, clearly stating the tool's purpose. It further distinguishes itself by specifying 'one append-only, hash-bound outcome is allowed per decision,' adding scope not present in sibling tools. Without ambiguity, the tool records decision outcomes.

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

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

The description implies the primary use case: after a Wu Wei decision is made, record the observed outcome. It also sets a clear constraint: only one outcome per decision, which guides when recording is appropriate. However, it does not explicitly reference alternatives like 'submit_evaluation' or state when not to use the tool.

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

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

With no annotations, the description carries the full burden. It describes what profiles can contain but does not disclose registration behavior such as overwriting, validation, permissions, or side effects. The 'never invents' note pertains to routing, not the registration action itself.

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

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

The description is two sentences: the first defines the purpose, the second lists the profile attributes and a constraint. It is compact and front-loaded, though the second sentence is a long enumeration.

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

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

For a registration tool with one required parameter, the description covers the core purpose and the main content of the profile. However, it lacks information about handling existing profiles, required prerequisites, and the return value (even though an output schema exists). The absence of annotations further reduces completeness.

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

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

Schema description coverage is 0%. The description does not mention 'profile' or 'request_id' by name, but it does explain what can be included inside the profile object (quality, reliability, costs, etc.), adding some meaning to that opaque structure. The optional request_id parameter is entirely unexplained.

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

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

The description clearly states the tool registers a 'caller-owned Wu Wei execution profile' and lists the profile types. The verb 'Register' plus the resource distinguishes it from routing and reporting siblings.

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

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

The phrase 'Routing never invents capacity or energy evidence' implicitly suggests registering profiles to provide such evidence before routing, but it does not explicitly state when to use this tool versus alternatives or provide any when-not-to-use guidance.

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

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

With no annotations provided, the description carries the full burden. It discloses important behaviors: it selects the least-burden route, considers multiple constraints, supports optional baselines, and may produce a no-work decision with no claimed result. It also promises a hash-bound decision receipt. These are meaningful behavioral details beyond the simple action of routing.

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

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

The description is four sentences, front-loaded with the core purpose, and each sentence adds distinct value: what it does, constraints, optional baselines, special decision case, and return behavior. No redundant or filler content.

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

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

For a tool with no annotations, a minimal schema, and an output schema, this description is quite complete. It covers purpose, key inputs, behavioral nuances, and output. It does not elaborate on request_id, but that parameter has a default and is likely incidental. The mention of a decision receipt and no-work scenario covers potential ambiguity.

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

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

Schema coverage is 0%, and the description does not explicitly describe the 'task' or 'request_id' parameters. However, it does mention specific fields within the task object ('allow_defer/value/urgency') and 'optional baselines,' which gives some semantic meaning to the otherwise generic task object. This partial compensation justifies a middle score.

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

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

The description clearly states the tool's purpose: 'Choose the least-burden eligible route for a task.' It specifies the verb 'choose' and the resource 'route for a task,' and lists hard constraints that distinguish it from siblings like 'best_next_steps' or 'compute_efficiency_report.' This is a specific, non-tautological statement.

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

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

The description implies when to use the tool: when a task must be routed based on constraints like quality, cost, latency, etc. It does not explicitly name alternatives or exclusion criteria, but the context is clear and no misleading guidance is given. It also mentions special cases like 'allow_defer/value/urgency' fields leading to a no-work decision, which further clarifies usage.

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

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

With no annotations, the description bears full burden. It discloses key behavioral traits: success/failure consequences on edges, growth/pruning rules, and safety axioms (NG1). However, it omits details like idempotency, rate limits, or authentication requirements.

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

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

The description is concise, with a front-loaded main verb and clear breakdown of evaluation fields. It uses three sentences effectively without redundancy. Slightly more structure (e.g., bullet points) could improve readability, but it is efficient.

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

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

Given the complexity (nested object, 3 params, output schema exists), the description covers the evaluation structure and return type (ledger events). However, it lacks details on error handling, idempotency, or prerequisites (e.g., agent must exist). The output schema is mentioned but not described, relying on the schema itself.

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

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

Schema description coverage is 0%, so the description must add meaning. It thoroughly describes the 'evaluation' parameter structure (task_id, success_score, optional fields). However, 'agent_id' and 'request_id' are not described, though agent_id is self-explanatory. Overall, it significantly aids understanding beyond the schema.

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

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

The description clearly states the verb 'Evolve' and the resource 'agent', specifying the input as a task outcome with detailed fields. It effectively distinguishes itself from sibling tools like create_agent or describe_agent by describing a mutation operation unique to this tool.

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

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

The description implies usage when a task outcome is available ('Evolve an agent with one task outcome'), but does not explicitly state when to use this over alternatives like compute_efficiency_report or route_task. No exclusions or alternative tools are mentioned.

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