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

With no annotations, the description carries the full burden of behavior disclosure. It mentions auditing categories but does not state whether the tool is read-only or produces a report, whether it modifies memory, or what side effects occur. The write_report parameter hints at report generation but is not explained, leaving behavioral expectations 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 a single, well-structured sentence that lists audit dimensions efficiently without redundancy or filler. Every phrase adds meaning, and the length is appropriate for the scope of a comprehensive audit tool.

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

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

The description lacks essential context for an agent to use the tool correctly. There is no mention of how results are returned, whether a report is written (despite the write_report parameter), or what actions an agent should take based on audit findings. With no annotations and no output schema, the description is too sparse to support autonomous 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% and the description completely omits the only parameter, write_report. The schema provides the name and default, but no meaning or effect is disclosed. Since coverage is low, the description should compensate, but it does not, leaving the agent to guess the parameter's role.

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 ('Audit') and clearly identifies the resource ('canonical memory') while enumerating precise audit categories (stale active notes, duplicate aliases, identity conflicts, etc.). This distinguishes it from sibling tools like memory_search or memory_status, which focus on retrieval or status rather than comprehensive auditing.

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 tool is used when a systematic audit of memory health is needed, but it provides no explicit guidance on when to choose this over sibling tools or when not to use it. There are no alternatives or exclusions mentioned, so usage context is only inferred from the verb and scope.

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

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

With no annotations, the description carries the behavioral burden and does well by disclosing that the operation is an append (non-destructive), durable, and rejects credentials. It lacks return-value or failure-mode details, but these core behavioral traits are useful and 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.

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

The description is two sentences, front-loaded with the primary action and immediately followed by a relevant content policy. Every clause adds value, with no fluff or repetition.

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

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

For a four-parameter tool with no output schema and no annotations, the description gives a clear purpose and category list but omits usage guidance, parameter semantics, and any indication of return behavior. It is minimally sufficient but leaves significant gaps.

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

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

Schema description coverage is 0%, and the description only repeats the category enum already present in the schema. It provides no additional explanation for the required title/content fields or the optional tags, so it fails to compensate for the low coverage.

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

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

The description clearly states the tool appends durable memory and enumerates supported categories (user, decision, project, knowledge, inbox), making the action and resource explicit. This distinguishes it from sibling tools like memory_search, memory_get, and memory_update by its verb 'append' and content scope.

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 capturing new memory by listing acceptable categories and a content policy, but it does not explicitly say when to prefer this over memory_update or other siblings. No alternatives, exclusions, or prerequisites are mentioned, so guidance is only implicit.

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

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

With no annotations, the description must carry the behavioral burden, but it does not. It fails to disclose potential side effects (e.g., whether write_report creates files), whether the tool performs read-only operations, how long it might take, or what the output looks like. The parameter write_report hints at a side effect, but the description does not explain it.

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 primary action. However, it is so brief that it omits essential details, which is a trade-off. Still, as a concise statement, it earns a high 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?

The tool has 2 parameters, no annotations, no output schema, and no parameter descriptions. The description does not explain return values, side effects, or how to interpret the metrics. Given the tool's evaluative nature, an agent needs to know whether it writes files, what data it accesses, and how to use the reported metrics. The description falls short.

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 adds no parameter information. The 'top' parameter likely relates to k in recall@k, but this is not explicitly stated. 'write_report' is completely unexplained. The agent must guess at their meanings from parameter names and defaults alone, 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's action: run the SecondBrain retrieval regression suite and report specific metrics (recall@k and mean reciprocal rank). This distinguishes it from sibling tools like memory_search and memory_get, which are for individual queries or retrieval, not for evaluating overall retrieval performance.

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 use case is implied: the tool is for evaluating retrieval performance. However, there is no explicit guidance on when to use it versus alternatives, nor any mention of prerequisites or exclusions. For example, it does not say 'use this instead of memory_search for benchmarking' or 'do not use in production with live data.'

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 for behavioral disclosure. It only says 'Read' and 'retrieve' — essentially restating the name. It does not mention max_chars truncation, error behavior for missing references, return format, or what distinguishes a 'SecondBrain note' from a 'historical catalog entry'.

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, focused sentence with no wasted words. It is front-loaded and easy to scan.

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

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

The tool has no annotations and no output schema, and the description is too thin to compensate. It omits critical details like parameter semantics (especially max_chars), return value structure, and domain context for 'SecondBrain note' vs 'catalog entry', leaving the agent under-informed for proper 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 the description must explain parameters. It provides an example reference (H0372) suggesting reference IDs, but it does not explain the `reference` parameter's allowed format or the `max_chars` parameter at all, leaving both underspecified.

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 reads a SecondBrain note or retrieves a historical catalog entry, giving a specific verb ('Read'/'retrieve') and resource. It distinguishes this from siblings like memory_search (searching vs retrieving by reference) and memory_update (read vs write).

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?

Usage is implied: use this when you have a reference like H0372 to fetch a specific note or catalog entry. However, it does not explicitly state when to prefer this over memory_search or other siblings, nor does it provide exclusions or alternative 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 of behavioral disclosure. It only states the action ('rebuild the index') without mentioning side effects, destructiveness, performance impact, or any requirements, leaving the agent uncertain about the tool's operational consequences.

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

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

The description is a single, front-loaded sentence with no wasted words. It efficiently communicates the core action, though it sacrifices detail 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?

For a simple one-parameter tool, the description covers the primary action and when to use it, but it is incomplete due to the missing parameter explanation and lack of behavioral details. The absence of an output schema reduces the need for return value documentation, but the parameter gap is significant.

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 entirely omits the 'embeddings' parameter, which is the only parameter in the schema. The schema provides only type and default, with no description, so the agent has no way to understand what this flag controls or when to set 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 uses the specific verb 'rebuild' and identifies the resource as the 'local keyword and semantic index', clearly distinguishing it from search, retrieval, and capture operations among siblings. It conveys exactly what the tool does without ambiguity.

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 'after substantial note changes' provides a clear context for when to use this tool, implying it is for maintenance after significant data modifications. It does not explicitly name alternatives, but the condition is specific enough to guide 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 carries the full burden of behavioral disclosure. It only states the return action, without indicating whether the operation is read-only, requires permissions, or has other side effects. No details about the 'recent' window or what constitutes a session are 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?

The description is a single, front-loaded sentence with zero fluff. It efficiently states the core purpose, earning a high score for structure.

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?

Although the tool is simple (one optional param, no output schema), the description lacks context about the return format, the meaning of 'per-tool session', and the effect of the 'top' parameter. This makes it minimally complete for an agent to invoke confidently.

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 defines one optional 'top' parameter (default 10), and the description does not explain it at all. Since schema coverage is 0%, the description offers no semantic meaning for 'top' beyond the name.

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 'Return' and identifies a clear resource: recent per-tool session memory logs. It distinguishes from sibling tools like memory_search or memory_get by focusing on recency, though the phrase 'per-tool session' is somewhat ambiguous.

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. It does not mention any exclusions, prerequisites, or scenarios where memory_search or memory_get would be preferable.

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 carry the behavioral disclosure. It tells the user the traversal depth (1-2 hops) and optional relation filtering, and the verb 'traverse' implies a read-only operation. However, it does not explicitly state that it makes no modifications, nor does it mention any permissions or rate limits.

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

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

The description is a single, front-loaded sentence that efficiently conveys the core functionality without redundant details.

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 4 parameters, no output schema, and no annotations. The description covers the primary action but does not describe the return value, error behavior, or the purpose of the 'top' parameter. It is adequate for a simple traversal tool but leaves gaps.

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

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

The schema describes 'reference' and 'relation' but not 'top' or 'depth'. The description adds meaning to depth ('one or two ontology hops') and relation ('optionally filtered by relation type'), but leaves 'top' unexplained. With 50% schema coverage, the description partially compensates but not fully.

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 the specific verb 'traverse' with a clear resource ('ontology hops around a canonical SecondBrain note') and mentions the optional relation filter. This distinguishes it from sibling tools like memory_search or memory_get, which are for search/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?

The description implies the tool is for exploring relationships between notes, but it does not explicitly state when to use it over alternatives or provide exclusions. It lacks guidance on scenarios where memory_search or memory_get might be more appropriate.

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

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

Since annotations are absent, the description carries the full burden. It discloses the hybrid retrieval method (keyword + semantic), but does not explicitly state read-only behavior, return format, or potential side effects. 'Search' implies read-only, but this is not confirmed, leaving some room for ambiguity.

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 with the main action ('Search the user's shared SecondBrain') and includes a usage note. Every word contributes to the meaning, with no waste or redundancy.

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

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

For a tool with no annotations and no output schema, the description is insufficient. It lacks any mention of return values, the meaning of 'top', or whether the operation is read-only. The purpose and usage are clear, but the overall context is incomplete for the agent to invoke it without assumptions.

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 does not mention either 'query' or 'top'. No meaning is added beyond the schema, leaving the agent to infer that 'query' is the search text and 'top' is the number of results, which is not explicitly stated.

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 identifies the tool as a search operation on 'the user's shared SecondBrain' using 'hybrid keyword and local semantic retrieval', which distinguishes it from sibling tools like memory_get or memory_recent. The verb 'Search' is specific and the resource is well-defined.

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

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

The phrase 'before substantive tasks' provides a clear contextual recommendation for when to use this tool, but it does not explicitly mention when not to use it or name alternative tools. This is a clear context but lacks exclusions or alternatives.

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

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

With no annotations, the description must disclose behavioral traits. It implies a read-only action with 'Check' but does not explicitly state that it has no side effects, what permissions are required, or any other behavioral details. It adds minimal context beyond the tool name, lacking disclosures about return format or operational boundaries.

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

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

The description is a single, concise sentence that front-loads the verb and specific objects. It contains no unnecessary words and is appropriately sized for the tool's simplicity.

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

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

The tool is simple with no parameters or annotations, but the description only states what it checks without explaining what 'status' means or what the output looks like. It is minimally adequate for an agent to understand the tool's primary function, but it lacks detail about the return value or any behavioral caveats.

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

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

The tool has zero parameters, so there is no parameter burden. The baseline of 4 applies, and the description correctly avoids mentioning parameters since none exist. The schema already trivially covers all parameters (none), and the description does not need to compensate.

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

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

The description uses a specific verb ('Check') and identifies the exact resources ('SecondBrain index' and 'automatic harvester status'), clearly distinguishing it from sibling tools like memory_search or memory_capture. This is a clear, specific statement of functionality.

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 any mention of prerequisites or conditions. It simply states what it does, leaving the agent to infer context from the tool name and siblings. No exclusions or alternative suggestions are given.

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

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

With no annotations, the description carries the full burden. It claims 'safely' appends but does not explain what 'safely' entails, what happens if the note does not exist, whether the note is created or modified, or any permission or format requirements. The behavioral disclosure is minimal and vague.

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, focused sentence that front-loads the core action and context. Every word contributes value, and there is 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 mutation tool with no annotations, no output schema, and three parameters, the one-sentence description is insufficient. It does not explain note identification, content format, heading semantics, error conditions, or how this tool behaves relative to its many siblings. The overall context is under-specified for reliable agent 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 description coverage is 0%. The description does not mention the parameters (path, content, heading) or explain how they map to the append operation. The parameter names are vaguely self-explanatory, but there is no clarification of what 'dated section' means in relation to the heading parameter or how content should be formatted. The description fails to compensate for the schema's lack of parameter details.

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 ('append'), the target ('existing Markdown note'), and the context ('SecondBrain'). It distinguishes from siblings by emphasizing the append/update operation, which contrasts with search/get/capture/rebuild tools.

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

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

No explicit guidance on when to use this tool versus alternatives like memory_capture or memory_rebuild. The implied use case (appending dated sections) is present, but there are no when-to-use or when-not-to-use instructions, nor any mention of sibling tools.

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