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

Annotations already signal read-only, idempotent, non-destructive behavior. The description adds value by disclosing that the call returns both supporting (hits) and contradicting (anti_hits) evidence plus a freshness verdict, and that this is combined into one call. It does not discuss failure modes or edge cases, but the output schema covers the return shape and the operation is simple.

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

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

One sentence packs the action, the example, the result summary, and the one-call characteristic with no filler. The key behavior is front-loaded before the 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?

For a simple three-parameter tool with full schema descriptions, read-only/idempotent annotations, and an output schema, the description is sufficient: it tells the agent what claim checking means and what to expect. Nothing critical for calling the tool correctly is missing.

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

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

Schema description coverage is 100%, so the schema already documents all three parameters. The description adds no parameter-level meaning beyond labeling the primary input as a claim, and the schema already gives an example for cue. 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?

Description names a specific verb ('Check') and resource ('claim ... against memory'), and the expected result ('hits + anti_hits + a freshness verdict in one call') makes it distinguishable from raw memory search/recall siblings. It goes beyond the tool name to define what a claim check actually produces.

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 purpose statement implies when to use this tool: when an agent has a claim to verify and wants evidence plus a freshness assessment in a single call. However, it does not name sibling alternatives (e.g., memory_search, memory_recall) or state when to prefer those instead, so the routing 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds context that the questions are 'queued by the sleep daemon' and are 'pending,' which is extra context beyond the annotations, but not extensive. It does not contradict annotations.

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

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

The description is extremely concise: three short sentences, front-loaded with the main action, then read-only note, then filter instruction. Every word earns its place with no redundancy or fluff.

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 list tool with one optional parameter, a rich set of annotations, and an output schema, the description is complete. It specifies the source (sleep daemon), state (pending), and filtering option, covering all necessary 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?

Schema description coverage is 100% (session_id has a clear description). The description mentions 'Filter by session_id' but does not add meaning beyond the schema. Baseline of 3 applies since the schema already documents the parameter well.

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

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

The description clearly states a specific action and resource: 'List pending curiosity questions queued by the sleep daemon.' It also notes the tool is read-only and can be filtered by session_id, distinguishing it from sibling tools focused on memory operations.

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?

Provides clear context on what the tool does (lists pending curiosity questions) and how to narrow results (filter by session_id). It lacks explicit alternatives or when-not-to-use guidance, but the read-only nature and filtering hint are useful.

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?

Annotations already cover read-only and idempotent behavior. The description adds valuable context beyond that: the "GLOBAL across all projects" scope, which could be surprising for users expecting project isolation, and the time-desc ordering. However, it does not disclose potential rate limits, pagination, or what happens when n exceeds the max, though those are partially covered by 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 a single, well-structured sentence that front-loads the core functionality, then adds the optional filter and global scope. Every clause adds value with no redundancy or filler.

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

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

For a simple read-only list tool with two optional parameters and a rich output schema, the description covers the essential behavior, scope, and ordering. The annotations and schema fill in safety and parameter details, making this sufficiently complete for a correct invocation.

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

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

Schema description coverage is 100% (n and session_id are fully described). The description only reiterates "Optional session_id filter," which adds no new meaning beyond the schema. It does not clarify edge cases like n=0 or negative values, but the schema already provides defaults and bounds.

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 "Returns" with a specific resource: "N most-recent user-turn records," including ordering (time-desc) and an optional filter. It also distinguishes itself by declaring "GLOBAL across all projects," setting it apart from project-scoped 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 description implicitly communicates when to use it (for recent user-turn records globally) but provides no explicit guidance on when not to use it or what alternatives might be better (e.g., memory_search for semantic recall, events_query for event logs). It lacks explicit exclusions or alternative tool references.

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?

Annotations already declare readOnly, idempotent, and non-destructive. The description adds context about 'user-visible events' and the 'kind whitelist', which are meaningful behavioral constraints beyond the annotations. 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?

Single concise sentence that front-loads the primary purpose and lists key filters. Every word earns its place; 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?

With full schema, annotations, and an output schema present, the description is sufficiently complete for a read-only query tool. It communicates the essential scope and filters; return format is handled by output schema.

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

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

Schema coverage is 100%, so baseline is 3. The description merely lists the optional parameters without adding details beyond what the schema already provides (e.g., ISO-8601 for since, enums for severity). No extra semantic 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 uses a specific verb 'Query' with a clear resource 'user-visible events' and scope ('kind whitelist'). This distinguishes it from sibling tools like memory_recall or episodes_recent.

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

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

The description clearly indicates this is the tool for querying events, with optional filters (since, severity, limit) and a whitelist constraint. It does not explicitly compare to alternatives, but the context is clear and there are no exclusions 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?

The description discloses one useful behavioral trait beyond the annotations: 'auto-dedups near-duplicates.' However, it does not explain side effects, persistence, merge/drop behavior, or response semantics. The annotations are all false, so they provide no additional safety or behavior hints, leaving the description with more responsibility than it fully carries.

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 filler. It states the core behavior, a key behavioral detail, and usage guidance, all in under 20 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?

For a tool with 14 parameters and several conditional agent-spawning fields, the text description is brief. The rich 100%-coverage schema and presence of an output schema compensate substantially, but the description itself does not hint at the background-agent registration/completion capabilities, so it is not fully complete.

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

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

Schema description coverage is 100%, so all 14 parameters already have detailed descriptions. The tool description adds no new parameter-level meaning, and with full schema coverage the baseline of 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?

Description states a specific action ('Capture a verbatim turn') and a precise resource/scope ('verbatim turn'), and it even carves out what it is not for ('not for minting standing-order directives'). This clearly distinguishes it from sibling memory tools like memory_recall or memory_consolidate.

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

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

The description gives explicit when-to-use guidance ('Use for corrections') and an explicit exclusion ('not for minting standing-order directives'). It stops short of naming an alternative tool to use for directives, so it lacks the full when/when-not/alternatives triad.

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?

Description adds value beyond annotations by stating 'Mutates store' (aligning with readOnlyHint: false) and specifying 'idempotent in one sleep window' (extending the idempotentHint). It also discloses the internal processes involved. No contradiction with annotations.

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

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

Two concise sentences with essential information front-loaded. Every word earns its place, with no redundancy or filler.

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

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

For a tool with one optional parameter, an output schema, and annotations covering safety/idempotency, the description provides sufficient context about purpose and effects. It could include more about when consolidation is appropriate, but the current level is adequate for selection and 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 coverage is 100% and the single parameter (session_id) has a complete description in the schema. The tool description adds no additional semantic meaning about the parameter, so 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?

Description clearly states the tool's function: 'Trigger sleep-cycle consolidation' and specifies three distinct processes (schema induction, FSRS decay, Hebbian pruning). This specific verb+resource combination distinguishes it from sibling tools like memory_recall or memory_reinforce.

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 this tool (when triggering sleep-cycle consolidation) but does not explicitly state when not to use it or mention alternatives. Clear context but no exclusions or comparisons to sibling tools.

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

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

Annotations already show this is a mutating, non-destructive operation. The description adds valuable behavioral clarity by explicitly stating that the old record is NEVER deleted and that the store is mutated. This goes beyond the raw annotation flags and sets correct expectations about data preservation.

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 immediately states the action, the key side effect, and the safety guarantee. Every clause earns its place; there is no redundant or vague filler.

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

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

Given the rich input schema, annotations, and presence of an output schema, this description is sufficient. It covers the essential behavioral contract—mutation, preservation of old records, and creation of a new contradicted record—without needing to restate schema details.

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

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

Schema description coverage is 100%, and each parameter including id, new_fact, cue_embedding, and epistemic_status already has a detailed schema description. The tool description contributes no additional parameter-level nuance, so the baseline of 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 uses a specific verb and resource: 'Mark a record contradicted' and clearly states the core effect—new fact stored as a NEW record while the old is never deleted. This differentiates the tool from siblings like memory_capture or memory_reinforce without needing to name them.

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 usage—contradicting a record while preserving the old fact—but gives no explicit guidance about when to prefer this over memory_capture, memory_reinforce, or other alternatives. There are no stated exclusions or conditional routing cues.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds that recall is 'verbatim' and that it 'Returns hits + anti_hits,' providing behavioral expectations beyond the annotations. It does not contradict annotations and adds 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 only two sentences, front-loaded with the action ('Recall'), and each clause carries distinct information: what it recalls, when to call it, and what it returns. No filler or redundancy.

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

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

Given the complete schema, output schema, and rich annotations, the description covers purpose, usage timing, and a return-shape hint. It could mention anti_hits semantics or caveats, but the schema and output schema fill those gaps. It is sufficient for a tool of this 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?

All 5 parameters are fully described in the schema (100% coverage), so the baseline is 3. The description identifies the 'cue' as the matching mechanism and mentions return behavior, but provides no additional parameter semantics beyond what the schema already offers.

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 ('Recall') and resource ('memories by cue') and lists content types ('decisions, preferences, prior discussion, rationale'). It distinguishes itself from siblings via 'verbatim' and the 'Call before a repository search' directive, though it doesn't explicitly name alternative 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?

It gives a clear context: 'Call before a repository search.' This tells when to use it but does not explicitly state when not to use it or name alternatives. Per rubric, that's a 4 (clear context, no 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds minimal behavioral context beyond the annotations, such as the TEM role->filler binding mechanism and the 'Read-only' statement, but these do not significantly enrich the agent's understanding of operational behavior. It does not contradict the annotations, though it also does not disclose return format or side effects beyond what annotations already imply.

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 three short phrases that convey purpose, safety, and usage preference. Every word adds value, and it is front-loaded with the core concept. No unnecessary filler or repetition exists.

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 a detailed input schema with all parameters documented, a rich output schema, and strong annotations. The description covers the core purpose and usage differentiation. It does not explain return values, but the output schema presumably handles that, and the overall definition is comprehensive enough for an agent to select and invoke the tool correctly.

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

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

Schema description coverage is 100%, and the parameter descriptions are detailed, including hard caps, budget behavior, and the meaning of omitted structure_query. The description text itself does not add further parameter semantics beyond relating the tool to 'role-filler queries', which is already evident from the schema. Therefore the baseline score of 3 is appropriate.

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

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

The description clearly states the tool performs structural recall via TEM role->filler bindings (BSC hypervectors), giving a specific mechanism and resource. It also explicitly distinguishes itself from the sibling tool memory_recall by noting it is preferred for role-filler queries, making its purpose unambiguous.

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

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

The description provides explicit usage guidance: 'Prefer over memory_recall for role-filler queries' directly tells when to use this tool over an alternative. The parameter schema further explains when structure_query is omitted, warning of an expensive full-corpus scan, which supplements the when-to-use 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?

The description discloses the mutation semantics ('Mutates edge weights') and reinforces the Hebbian reinforcement idea, which adds detail beyond the readOnlyHint=false annotation. It does not contradict the annotations; idempotency is already declared in the schema and annotation.

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

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

Three short, meaningful sentences: the action, the mutation effect, and the usage condition. No fluff or repetition that wastes tokens.

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

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

For a simple two-parameter tool with an output schema and annotations, the description plus schema provide enough to invoke it correctly. It could be more explicit about when not to use it relative to memory_recall or memory_consolidate, but this is not a critical gap.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds only contextual meaning to 'ids' via 'co-retrieved record ids' but does not add parameter-level details that the schema already lacks.

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 ('Boost') with a clear resource ('Hebbian edges among co-retrieved record ids') and states the core effect ('Mutates edge weights'). It distinguishes this from sibling memory tools by focusing on edge-weight reinforcement rather than search, capture, or recall.

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

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

It explicitly says 'Use when two records co-answered', giving a clear trigger condition. It does not name exclusions or alternative sibling tools, so it does not fully meet the 5-level bar.

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?

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable context by stating that results are 'hints to verify' and that the tool does not substitute for a full repository search. This goes beyond the annotations and clarifies the reliability of the output.

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 purpose, usage, and a behavioral caveat. Every clause adds value: 'Use for code/doc search' (purpose), 'returns hints to verify' (behavior), and 'never replaces a repository search' (limitation). No 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 presence of 2 well-documented parameters, annotations, and an output schema, the description covers the essential aspects: what it does, when to use it, and a key limitation. It does not explain return values, but the output schema handles that. Minor gap: no explicit mention of how this differs from memory_recall siblings, but overall the description is sufficient for an agent to select and invoke the tool.

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

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

Schema description coverage is 100%, so the schema already documents both parameters (query and k) with descriptions. The description does not add additional meaning specific to the parameters; it only mentions 'code/doc search' which indirectly implies the query type, but that is marginal. Baseline 3 is appropriate.

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

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

The description states a clear verb and resource: 'Use for code/doc search'. It distinguishes itself from a repository search by saying it 'never replaces a repository search', but does not explicitly differentiate from sibling memory tools like memory_recall or memory_temporal_recall. Still, the core purpose is clear.

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

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

The description provides explicit when-to-use context ('Use for code/doc search') and a when-not-to-use ('never replaces a repository search'). However, it does not mention alternatives or explicitly contrast with sibling tools, so it falls short of the full 'explicit alternatives' bar.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the 'Read-only' phrase is redundant. However, the description adds valuable behavioral detail by explaining that as_of bounds the records side and changed_since filters the events side, clarifying the dual-sided temporal semantics beyond the 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 a single, efficient sentence with a colon introducing the key mechanics. Every phrase carries meaning, and the front-loaded 'Time-travel recall' immediately conveys the tool's niche. No 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 output schema exists, return value details are not needed. The description covers the core behavior (the two bounds) and mentions the read-only nature, which aligns with annotations. It omits discussion of cue and limit, but the schema provides those. Overall, it is complete for a read-only temporal query 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 already covers all parameters (100% coverage), giving a baseline of 3. The description adds meaning by mapping as_of to the records side and changed_since to the events side, helping the agent understand how these parameters relate to the two outputs. This semantic grouping exceeds the schema's individual 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?

The description clearly states the tool's purpose with a specific verb ('recall') and resource ('records' and 'events') while uniquely specifying temporal scoping via 'as_of bounds records, changed_since filters events'. This distinguishes it from siblings like memory_recall and memory_search by emphasizing its temporal nature.

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 temporal use cases but does not explicitly state when to use this tool over siblings like memory_recall or events_query. No exclusions or alternative recommendations are provided, leaving the agent to infer usage context from the temporal keywords.

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 annotations already disclose readOnly=false, destructive=false, and idempotent=true; the description adds that the knobs are sealed and that get/set returns a value. It does not describe set-side effects such as validation, persistence, or deferred knob behavior, but the annotations carry the core safety profile.

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 plus a compact clause, with each component earning its place: purpose, knob inventory, operation mode, and return behavior. There is no filler or repetition of schema 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 3 parameters, an output schema, and complete schema coverage, this description is sufficient: it states the resource, operation, knob list, and return. It could mention error cases or dynamic/deferred knob behavior, but the schema and annotations already cover much of the 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?

Schema description coverage is 100% and the schema already documents operation, knob, and value with rich details, including 'get' with no knob returns all live+deferred values and set requires both fields. The tool description adds no new parameter detail, so the baseline score is appropriate.

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

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

The description clearly states the tool 'Read or write a profile knob' and names the two operations, get and set. It further specifies the exact sealed knob set (9 AUTIST + wake_depth), which makes the purpose concrete and distinguishes it from the unrelated sibling 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?

It gives clear context that the tool is used to access/update profile knobs and that 'operation' selects read vs write. It doesn't explicitly name alternatives or when-not-to-use cases, but the tool's domain is narrow enough that no sibling overlap is apparent.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful context about the source (sleep consolidation) and the Tier-0 + Tier-1 restriction, but it does not disclose any further behavioral traits such as return format or side effects. This aligns with the calibration example where annotations carry the main burden and the description adds moderate value.

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, with the core action and scope front-loaded in the first sentence. The second sentence adds the read-only note and filter parameters with no 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 tool's simplicity (two optional parameters, full schema descriptions, an output schema, and rich annotations), the description adequately covers the essential aspects: what it lists, the source, safety, and filtering. No significant information is missing for an agent to select and invoke the tool correctly.

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

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

The input schema already provides 100% coverage for both parameters, including defaults and semantics. The description only echoes 'Filter by domain and confidence_min' without adding any additional meaning beyond what the schema provides, so the 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 uses a specific verb 'List' with a clear resource 'induced schemas' and narrows scope to 'Tier-0 + Tier-1 from sleep consolidation.' This not only states what it does but also distinguishes it from sibling memory tools like memory_recall or memory_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?

The description clearly indicates the tool is read-only and mentions the two filter dimensions (domain and confidence_min), which provides clear context for when to use it. However, it does not explicitly name alternatives or exclusion criteria compared to sibling tools, so it stops short of a 5.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds a specific behavioral guarantee that 'sigma never toggles retrieval', which is useful context beyond the annotations. It also clarifies the read-only nature without contradicting 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 a single, information-dense sentence. It front-loads the core purpose, lists the key output components, and adds a critical behavioral note all in one concise statement with no filler.

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

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

With an output schema present and zero parameters, the description sufficiently covers the tool's purpose and behavior. The mention of 'sigma never toggles retrieval' addresses a potential concern, and the read-only diagnostic label sets accurate expectations. No significant gaps are apparent.

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

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

The tool has zero parameters, so the baseline score is 4. The description needs no parameter explanations; it appropriately focuses on output fields instead.

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 providing a snapshot of memory-graph topology, listing the specific fields (N, C, L, sigma, community_count, regime). It differentiates itself from sibling memory tools by being a read-only diagnostic, not a retrieval or mutation 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 explicitly labels it as a 'read-only diagnostic', making the intended use case (inspecting topology) clear. It does not mention explicit alternatives, but the context is sufficient given the tool's simplicity and zero parameters.

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