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

No annotations provided, so description carries full burden. It only mentions returning a default config but does not disclose any side effects, permissions, or whether it is a read/write operation. For a deprecated tool, minimal behavioral context is given.

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?

Exceptionally concise: one sentence plus deprecation notice. Every word serves a purpose, with the deprecation and replacement placed front and center.

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 it is deprecated and has no parameters, the description covers the basics. Output schema exists to explain return values. Slight lack: does not elaborate on use cases for unknown agents, but sufficient for a deprecated 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?

Tool has zero parameters, and schema coverage is 100%. The description correctly includes no parameter details because none exist. Baseline of 4 is appropriate as description adds no unnecessary information.

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

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

Description clearly states the tool is deprecated and directs to 'agent_handshake' instead. It specifies the action ('Generic agent onboarding') and output ('Returns default config for unknown agents'), making the purpose unmistakable.

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

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

Explicitly marked as deprecated with a direct replacement ('use agent_handshake instead'), providing clear when-to-use and when-not-to-use guidance. Also implies it is for unknown agents, but main guidance is the deprecation.

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

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

No annotations are provided, so the description carries full burden. It states the tool returns 'optimal config' but does not disclose if it modifies state, requires permissions, or what happens on repeated calls. For a handshake/onboarding tool, the behavior is partly inferred but not fully transparent.

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

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

The description is concise: a clear lead sentence followed by a bullet-like argument list with examples. It is front-loaded with purpose and usage instruction, and every sentence adds value without redundancy.

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

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

Given the tool's simplicity (handshake), zero required params, an output schema (not shown but present), and many siblings, the description fully covers context: what to pass, calling order, and expected return ('optimal config'). It is complete for its role.

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% (no schema descriptions), yet the description lists all 7 parameters with examples (e.g., 'model: Your model ID (e.g. 'claude-opus-4-6')'). This adds substantial meaning beyond the bare schema, though the format of defaults in examples is slightly inconsistent.

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

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

The description clearly states it is 'Personalized agent onboarding' to 'Declare your environment and get optimal config' and instructs to 'Call this FIRST when connecting to MidOS.' This sets a specific verb+resource scope and distinguishes it from siblings by positioning it as the mandatory initial step.

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

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

The description explicitly says 'Call this FIRST when connecting to MidOS' and advises to 'Pass as much info as you know' while noting 'Unknown fields can be left empty -- you'll get sensible defaults.' It does not explicitly exclude alternatives like agent_bootstrap, but the clarity of when to use (at connection start) is strong.

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

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

No annotations are provided, so the description must disclose behavioral traits. It states 'parse' but does not indicate whether the tool is read-only, what file types are supported, or how errors (e.g., missing file) are handled. The purpose is clear, but behavioral details are sparse.

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 one sentence and an args section. It is front-loaded with the main purpose. The structure is efficient, though it could benefit from slightly more organization (e.g., bullet points).

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 presence of an output schema, the description does not need to detail return values. However, it omits important context such as supported programming languages, file size limits, and error behavior. This makes it adequate but incomplete for a code parsing 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 description explains the single parameter 'file_path' as a path to a code file to chunk, adding meaning beyond the schema's type-only definition. Since schema description coverage is 0%, the description compensates well by providing context.

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

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

The description clearly states the tool's function: parsing code files into semantic chunks (functions, classes, methods) for RAG retrieval. The verb 'parse' and resource 'code file' are specific, and the tool is distinct from sibling tools like 'search_knowledge' which focus on searching.

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

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

The description implies use for RAG retrieval but lacks explicit guidance on when to use or when not to use this tool. No alternatives are mentioned, and the context does not clarify when this tool is preferred over siblings.

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

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

No annotations provided, so description carries full burden. It mentions vector similarity but does not state whether it's read-only, error conditions, or permissions needed. Minimal behavioral disclosure.

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

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

Extremely concise: two sentences and two arg descriptions with no fluff. Every sentence adds value.

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 an output schema (true), the description need not explain return values. However, it could mention the type of results (e.g., experiences with similarity scores). Still, adequate for invocation.

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

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

Schema description coverage is 0%, so description compensates. It provides clear meanings for query ('Search query describing the experience/task') and limit ('Maximum results (default: 5)'), adding value beyond the schema.

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

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

The description clearly states the tool searches episodic memory for similar past experiences using vector similarity. This distinguishes it from siblings like episodic_store (store) and semantic_search (general semantic search).

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

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

No explicit guidance on when to use this tool vs alternatives. The description does not mention when not to use it or compare to siblings like search_knowledge or semantic_search.

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

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

No annotations provided, so description must disclose behaviors. It only describes the action and parameters, but no details about side effects, overwrite or append behavior, persistence guarantees, or error handling.

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

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

The description is extremely concise: one sentence summary followed by a compact args list. No wasted words, front-loaded with purpose.

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

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

Given the tool's simplicity and presence of an output schema, the description covers basic usage but lacks key context like idempotency, concurrency behavior, or whether duplicates are allowed. It is minimally complete.

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

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

With 0% schema description coverage, the description adds clear meanings for all three parameters (task_type lists allowed values, input_preview explains what it represents, success indicates outcome). This compensates well for the schema gap.

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

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

The description clearly states the verb 'Store' and resource 'episodic memory/reflection', and it is distinguishable from sibling 'episodic_search' which is for retrieval.

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

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

No guidance on when to use this tool versus alternatives, no exclusions or prerequisites mentioned. The description only explains what it does, not when to use it.

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

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

No annotations provided, so the description carries full burden. It only states it 'gets' a document, with no disclosure of side effects, permissions, or return behavior beyond the basic action.

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

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

The description is extremely concise, front-loading the core purpose. Every sentence serves a purpose without wasted words.

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

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

Given the simplicity of the tool (single parameter, output schema exists), the description is mostly adequate. However, it does not explain what a 'EUREKA breakthrough document' is, which may require external knowledge.

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%, but the description adds value by providing examples of the 'name' parameter (e.g., 'EUREKA_CACHE_SEMANTICA' or 'ATOM_001'), which clarifies the expected format.

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

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

The description clearly states it retrieves a specific EUREKA document. It uses a verb+resource pattern and distinguishes from siblings like 'get_protocol' and 'get_skill'. However, 'EUREKA' is not defined, which slightly reduces clarity.

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. The description lacks explicit context for when it is appropriate or exclusion criteria for siblings.

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

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

The description implies a read operation but does not disclose side effects, authentication requirements, or error behavior. With no annotations, this is insufficient for a safe selection.

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 one sentence and an argument section. It is front-loaded and avoids unnecessary 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 presence of an output schema and only one parameter, the description is minimally adequate but does not cover scenarios like missing protocol or return format.

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 for the 'name' parameter, but the description provides an example ('PROTOCOL_NEURAL_LINK') and states it's a protocol name. This adds some meaning beyond the schema, but not full semantics.

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

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

The description clearly states 'Get a specific protocol document,' which specifies the verb and resource. It distinguishes from sibling tools by the resource name 'protocol', but lacks additional differentiation context.

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

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

No guidance is provided on when to use this tool versus alternatives like 'get_eureka' or 'get_skill'. The description does not mention context or exclusions.

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

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

No annotations are provided, so the description must fully disclose behavior. It only states retrieval by name, without mentioning error handling (e.g., if name not found), access restrictions, or data format. Minimal 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 short and front-loaded with the core purpose. The Args section is somewhat redundant with the schema but keeps it readable. No wasted words; however, the redundancy prevents a perfect score.

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, so return values need not be explained. However, the description lacks context about what a skill/capability document is or contains. For a single-parameter tool, it is minimally adequate but could be more informative.

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

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

Schema description coverage is 0%, so the description must compensate. It adds an example ('RAG_SYSTEMS_2026_SOTA') and clarifies that 'name' is a skill name, but does not define valid naming conventions or document structure. Slightly better than the schema alone.

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 specifies the action 'Get' and the resource 'specific skill/capability document', clearly distinguishing it from sibling 'list_skills' which would return multiple skills. The verb and object are precise.

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 'list_skills'. There is no mention of prerequisites, context, or what constitutes a valid skill name, leaving the agent to infer 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?

No annotations are provided, and the description only says 'Get', implying a read operation. It does not disclose any behavioral traits such as authentication requirements, rate limits, side effects, or response format. Since there are no annotations to contradict, there is no contradiction.

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

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

The description is extremely concise, consisting of a single sentence and one line for the parameter. It is front-loaded and contains no redundant or extraneous information.

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

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

Despite having only one parameter and an output schema, the description is insufficient. It does not explain what a 'truth patch document' is or what the tool returns, leaving the agent without enough context to use it effectively. Sibling tools like get_eureka or get_protocol likely have similar descriptions, but this one lacks differentiation.

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 required string parameter 'name' with 0% description coverage. The description adds semantic value by labeling it as 'Truth patch name' and providing an example. However, it does not explain the format or constraints of the name beyond the example.

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

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

The description clearly states the verb 'Get' and the resource 'specific truth patch document'. It provides an example parameter value, but does not distinguish it from sibling tools like get_eureka or get_protocol, which also retrieve specific documents.

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

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

No guidance is given on when to use this tool versus alternatives. The description does not mention conditions, exclusions, or prerequisites for using get_truth over other 'get' tools.

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

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

With no annotations, the description must convey behavioral traits. 'Get current status' implies a read operation but does not explicitly state it is safe, side-effect-free, or whether authentication is needed. It adds minimal value beyond the tool name.

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

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

The description is a single, front-loaded sentence with no wasted words. It efficiently communicates the tool's purpose.

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

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

For a parameterless status read with an output schema, the description is sufficiently complete. It could mention the nature of the status (e.g., health metrics), but the output schema likely covers that.

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

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

There are zero parameters (100% schema coverage), and the baseline is 4. The description does not need to add parameter information since the schema already handles it.

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

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

The description clearly states the tool retrieves the current status of the Midos hive system. It distinguishes itself from sibling status tools like pool_status and project_status by specifying 'hive system', though it could elaborate on what that encompasses.

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 pool_status or project_status. The description lacks usage context or exclusion criteria.

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

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

No annotations are provided, so the description carries full burden. It notes stack-based prioritization but lacks details on side effects, auth, or ordering beyond 'prioritized.'

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 brief but includes a structured Args section. The main purpose is front-loaded in two clear sentences, though the Args section could be more compact.

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, the description need not cover return values. It adequately explains parameters and list behavior; missing pagination hints but acceptable for a simple tool.

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

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

Schema coverage is 0%, but the description adds meaning by defining 'filter' as optional skill name filter and 'stack' as comma-separated with prioritization behavior, exceeding the bare schema.

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

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

The description 'List all available skills/capabilities' uses a specific verb (List) and resource (skills/capabilities), clearly distinguishing it from sibling 'get_skill' which retrieves a single skill.

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

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

The description explains optional filter and stack parameters but does not explicitly state when to use this tool vs alternatives like get_skill. It implies listing all, but no direct when-not guidance.

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

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

The description indicates a read-only operation ('Get statistics'), which is appropriate for a tool with no parameters. Since no annotations are provided, the description adequately conveys the tool's safety and intent, though it could explicitly state it has no side effects.

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

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

The description is a single, efficient sentence of 11 words that directly states the tool's purpose. No extraneous information is included.

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

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

Given the tool has no parameters and an output schema exists (not shown), the description is sufficiently complete. It identifies the two key statistics areas (LanceDB chunks, cache status). Minor improvement could be mentioning additional output details, but the schema likely covers that.

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

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

The tool has no parameters, and schema description coverage is 100% (empty schema). The description does not need to add parameter meanings, earning a baseline score of 4 for parameterless tools.

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

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

The description clearly states it retrieves statistics about the Midos memory system, specifically mentioning LanceDB chunks and cache status. This verb-resource pair is distinct from sibling tools like hive_status or pool_status, which target different subsystems.

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 memory system statistics are needed, but does not explicitly guide when to use this tool versus alternatives like hive_status or pool_status. No exclusions or conditionals are provided.

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

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

No annotations provided; description does not disclose behavioral traits like side effects, blocking behavior, or response semantics. Only lists actions but not effects.

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

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

Purpose front-loaded but the Args section adds length. Could be more compact without losing clarity.

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

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

Missing behavioral context and usage scenarios. No output schema shown in evaluation; description does not cover return values. With no annotations, the description should provide more detail.

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 has 0% description coverage, so the description adds meaning by explaining each parameter's role ('action type', 'topic', 'summary', 'affects'). However, lacks detailed constraints (e.g., valid action values).

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 signals an action to a multi-instance coordination pool, with a specific verb and resource. It lists parameters adding clarity, but does not explicitly differentiate from sibling tools like 'pool_status' or 'hive_status'.

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. No context on prerequisites or typical use cases.

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 fully. It only states it gets status and activity, but does not mention it is read-only, non-destructive, or any prerequisites. The agent lacks crucial 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?

Description is a single sentence, concise and front-loaded. However, it could be slightly more descriptive without being verbose.

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

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

The description is minimal but an output schema exists (not shown). It mentions 'status and recent activity' which provides some context, but lacks detail on the nature of the output (e.g., health indicators).

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?

Tool has zero parameters, so schema coverage is 100%. Baseline is 4; no additional parameter information is needed, and description does not repeat schema content.

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

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

Description clearly specifies the tool retrieves status and recent activity of a multi-instance coordination pool, using a specific and distinguishable verb and resource. It differentiates from sibling tools like 'hive_status' by focusing on 'pool' coordination.

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 'hive_status' or 'project_status'. The description lacks context for usage or exclusion.

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

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

No annotations are provided, so the description carries the full burden. It thoroughly describes the behavior: real-time stats, vector health, available MCP tools with examples, research queue, and tips. There is no contradiction with annotations as none exist.

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

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

The description is concise and well-structured: a title line, a bullet list of what the tool returns, and a closing sentence. Every sentence adds value, and the format is easy to parse.

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

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

Given no parameters and the presence of an output schema (though not provided), the description is complete. It lists all the return items explicitly, making it sufficient for an agent to understand the tool's purpose and 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?

There are no parameters (0 params), so the baseline is 4. The description does not need to explain parameters, and it provides no parameter information, which 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 is very specific: 'Live MidOS system status + quick-start guide for your agent.' It lists exactly what it returns (stats, health, tools, queue, tips) and clearly states it is a '/status command,' distinguishing it from sibling tools like hive_status and memory_stats.

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

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

The description explicitly says 'Call this anytime' and 'Use it to orient yourself and teach your agent how to leverage MidOS,' providing clear guidance on when to use it. It lacks explicit 'when not to use' or alternatives, but the context is strong enough.

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 must disclose behavioral traits. It states the tool queues a video and that transcription/insight extraction will follow, but does not specify if it's asynchronous, error handling, rate limits, or any side effects.

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

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

The description is concise with one introductory sentence and a parameter list. It avoids fluff but the parameter list could be more formally integrated with the schema.

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

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

Given the low complexity (2 params, no enums), the description covers basic purpose and parameters. However, it lacks behavioral details and usage guidelines, which are important for an agent to use it correctly.

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

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

Schema coverage is 0%, so the description adds meaning by explaining the url parameter as the YouTube URL and priority as high/normal/low with a default. This is helpful beyond the schema's type and default fields.

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 queues a YouTube video for research and that Midos will transcribe and extract insights. It uses specific verbs and resource, and distinguishes from sibling tools which are mostly about knowledge search and agent management.

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

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

The description implies usage for researching a YouTube video but provides no explicit guidance on when to use this tool versus alternatives, no prerequisites, and no mention of 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.

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

No annotations are provided, so the description must disclose behavioral traits. It only states the tool searches, but offers no details on mutation, permissions, rate limits, or result characteristics, which is inadequate for a search tool with no annotations.

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

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

The description is concise and front-loaded with the purpose, followed by a clear list of arguments. It contains no fluff, though the lack of structure for additional context is acceptable given its 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 existence of an output schema, return values need not be explained. However, the description omits context like ranking criteria or scope of the knowledge base, and fails to address the presence of multiple sibling search tools, leaving the picture incomplete.

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?

With 0% schema description coverage, the description carries the burden but merely rephrases parameter names and types. It adds minimal value beyond the schema, lacking details like query format or the effect of max_results on output.

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

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

The description clearly states the tool searches the Midos knowledge base for relevant information, specifying the resource and action. However, it does not differentiate from sibling search tools like semantic_search or episodic_search, which may cause confusion.

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

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

The description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or excluded scenarios. This leaves the agent without decision support.

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

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

No annotations provided, so description carries burden. Discloses use of LanceDB vectors, Gemini embeddings, and boosting behavior for stack filter. However, does not state that it is a read-only operation, nor mentions any rate limits, authentication, or that it does not modify data.

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?

Very concise: three sentences plus Args list, front-loaded with purpose. Every sentence adds value with no redundancy.

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

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

Given the presence of an output schema (not shown but indicated true), the description adequately covers functionality: vector search, embedding model, parameter details, and boosting. No gaps for an agent to misuse or misinterpret.

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%, but description adds rich meaning for all 3 parameters: query example, top_k default, and stack filter with comma-separated example and boosting effect. This completely compensates for the lack of schema descriptions.

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

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

Clearly states it is a 'semantic search' using vectors, with specific verb+resource. Differentiates from keyword search and implies distinction from siblings like search_knowledge.

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

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

Mentions 'More intelligent than keyword search' but does not explicitly state when to use this tool vs alternatives like search_knowledge, episodic_search, or what constitutes a query suitable for semantic search. No exclusions or explicit context provided.

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