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

With no annotations provided, the description carries the full transparency burden. It explains that the tool returns everything currently believed, grouped, with fact ids. As a 'list' operation, read-only behavior is strongly implied, and no side-effect or permission concerns are suggested.

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 tight sentences: the first states the action and output format, the second gives the intended use. Every clause 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 zero-parameter tool with no output schema, the description is nearly complete: it names the action, the data scope, output grouping, fact ids, and the use case. It does not mention pagination or potential large result sizes, but that is a minor omission for a simple audit-listing 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 tool takes zero parameters, so the input schema fully covers parameter semantics. The description adds no parameter-specific meaning, but none is needed; the baseline of 4 applies because there is no parameter burden to carry.

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') and a clear resource ('everything currently believed about this project'), and indicates the output is grouped with fact ids. It clearly implies a comprehensive audit listing, but it does not explicitly name or contrast sibling tools like 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 provides an explicit use case: 'Use to review or audit the memory.' This gives clear context for when to call the tool, though it does not mention when not to use it or point to 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 provided, the description carries the full behavioral burden. It discloses the key non-obvious behavior: the record is retired rather than deleted, and the audit chain is preserved. This is valuable context beyond the mere 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 one concise sentence that front-loads the primary action and then adds the critical nuance about retirement versus deletion. Every word earns its place.

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

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

For a single-parameter tool with no output schemahaving, the description covers the essential purpose and the most important behavioral caveat. It lacks explicit context about return values or error conditions, but the tool is simple enough that 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?

The schema has no parameter descriptionscars, and the description only mentions factKey by name. It confirms that factKey identifies the fact to suppress, but adds no detail about the expected format or provenance of the key. The single-parameter simplicity keeps this at an acceptable level.

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 action ('Suppress') and a specific resource ('a fact') with the identifying key. It also clarifies the semantic distinction from deletion, which helps distinguish it from sibling tools like remember and 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?

The description implies when to use the tool: when you have a factKey and want to suppress a fact. However, it provides no explicit guidance on when not to use it or which alternative sibling tool 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?

With no annotations, the description carries the disclosure burden. It reveals that each handoff supersedes the previous one, that the handoffId can be walked via why for auditing, and that clear=true retires the active handoff. This gives the agent awareness of mutation and chain behavior, though it does not fully describe the return value or error cases.

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 dense sentences with no filler. The main action and payload are front-loaded, followed by chain behavior and clear mode. The phrase 'why on the returned handoffId walks it' is slightly jargon-heavy but still efficient and informative.

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 4 optional parameters, no output schema, and no annotations, the description covers when to use it, what payload to pass, how clearing works, and what happens to the next session. It lacks an explicit example and full return contract, but those are not essential for 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 coverage is 0%, so the description must compensate. It does: 'summary, open questions, and next steps' maps to the three content parameters, and 'Pass clear=true' explains the boolean. Constraint details like maxLength and maxItems remain in the schema, which is acceptable.

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 and resource: 'Record where this session stopped' with a concrete payload (summary, open questions, next steps). This distinguishes it from sibling memory tools like remember/recall by focusing on session handoff and supersession rather than general memory storage/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?

It explicitly says when to use the tool: 'before ending or compacting' a session. It also explains the alternative clear mode: 'Pass clear=true to retire the active handoff instead.' It does not name sibling alternatives to avoid, but the usage context is clear 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?

No annotations are present, so the description must carry behavioral disclosure. It explains the output is a distilled digest plus believed facts, recent events, and a budget report of omissions, and frames the result as packed into a character budget. It does not explicitly confirm read-only behavior, but 'Retrieve' and the absence of mutation language make the safety profile reasonably clear.

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 sentences with no filler; the action is front-loaded, the return content is listed compactly, and the usage trigger is in a short final clause. Every sentence earns its place.

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

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

For a simple two-parameter retrieval tool with no output schema, the description covers what it returns and when to call it. The main gaps are parameter-level detail (maxChars semantics, default behavior) and explicit read-only confirmation, but the core invocation context is present.

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

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

Schema description coverage is 0%, so the description must add the meaning. It does so at a high level: 'query' is the relevance input and the output is 'packed into a character budget,' which maps to maxChars. However, it never names maxChars, states what happens when it is omitted, or describes how the budget size changes results, so it stops short of full compensation.

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?

States a specific verb ('Retrieve') and resource ('project memory relevant to a query') and adds the return shape. It does not explicitly differentiate from sibling tools like facts, but the general recall scope is clear enough for selection.

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 explicit temporal guidance: call at the start of a session or before relying on past context. It does not state when not to use it or name alternatives, so it is clear context but not full routing.

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 meaningfully adds that the operation is deterministic, audit-tracked, has a default 500-character cap, and that consolidate=true allows up to 2000 characters with background distillation. It does not cover conflict resolution or return behavior, but the disclosed traits go well beyond the raw 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?

Three sentences with zero fluff: the first states purpose, the second provides usage context, the third covers parameter behavior. The most important information is front-loaded, and every sentence contributes meaningful detail 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?

For a two-parameter tool with no output schema and no annotations, the description covers the core behavior, the default vs. consolidated path, and usage context. It omits return value and error handling, which are minor for this simple store operation, so it is almost 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 0%, so the description must compensate for both parameters. It elegantly explains that 'text' defaults to a 500-character note unless consolidate=true, which then accepts up to 2000 characters and gets distilled in the background. This adds crucial semantics about the consolidate flag that the schema alone could not convey, effectively documenting both parameters.

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

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

States a specific verb and resource ('Store a durable fact') and clearly scopes the use to project/user preferences, decisions, and constraints for the next session. The purpose is instantly distinguishable from sibling tools like recall (retrieval) and forget (deletion), even without naming 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?

Provides explicit guidance on what to store ('preferences, decisions, constraints, and anything worth knowing next session'), giving clear context for when to use the tool. However, it does not explicitly mention when not to use it or point to alternative siblings for retrieval or deletion, so it falls short of full routing 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?

No annotations are present, so the description carries the full burden. It discloses the tool's output behavior (source evidence and full version chain, including superseded and retired versions), and 'Explain' strongly implies a read-only operation. However, it does not explicitly state that no state is modified or describe behavior for unknown/invalid factIds.

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 with no filler. The main purpose is front-loaded, and the usage hint about factId follows naturally. Every sentence earns its place.

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

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

For a low-complexity tool with one parameter and no output schema, the description covers what the tool returns and how to get the required input. Minor gaps remain: no explicit no-side-effects statement and no error behavior, but these are relatively small given the simple read/explain nature of 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?

The schema only provides type and minLength for factId, with no description. The tool description adds meaningful guidance by saying to pass a factId from facts or recall, giving the parameter a clear source. For a single simple string parameter, this is sufficient, though it lacks format examples or edge-case guidance.

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 ('Explain') and resource ('fact'), and spells out exactly what is returned: source evidence and the full version chain including superseded and retired versions. This clearly distinguishes it from siblings like facts or recall, which focus on retrieval rather than provenance.

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 clear context: use this tool when you need to understand why a fact is believed and what evidence/version history supports it. It also tells the agent where to obtain the required factId ('from facts or recall'), but it does not explicitly state when not to use it or name alternatives.

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