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

With no annotations, the description carries the full burden and does so thoroughly. It discloses the read-only nature, the side effect that the lookup is recorded, and the security behavior of returning a signed deny for both non-existent and other-tenant refs to avoid information leaks. This is exemplary behavioral disclosure.

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

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

The description is dense but well-organized, moving from purpose to usage, return fields, and edge-case behavior. It is longer than minimal, yet every sentence contributes essential information and nothing feels redundant or off-topic.

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 schema, the description fully explains the return shape: record, effect, finding, witnessClass, guarantee, warnings, trustRoot, and the held-call pair case. Error semantics are also covered with the signed-deny behavior. An agent has everything needed to call and interpret 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 coverage is 100%, so baseline is 3, but the description adds practical semantics beyond the schema: the ref is the one returned by an earlier call, or the tail of a denied/deferred answer. This helps the agent locate the correct value to pass.

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: reads a signed ledger decision by ref and explains it. The tool's focus on auditing decisions is clearly distinct from sibling tools handling memory, messaging, and spending, so an agent can tell them apart immediately.

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

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

Explicitly says when to use it: to check what the body decided about an earlier call and whether the effect matched, before repeating or reporting on it. It also notes the lookup is recorded, which is a useful side-effect warning. No alternatives are named, but the siblings are unrelated so exclusions are not necessary.

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, and it delivers: it discloses policy-gate behavior, signed decision records, cross-tenant deny behavior, exact JSON return shapes, stale/notYetValid handling, and not-found errors. This is unusually thorough for a read tool.

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 dense but every sentence earns its place: purpose first, then usage, then safety/behavior, then return formats and edge cases. There is no filler, and the structure front-loads the single most important fact: what the tool reads.

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 one-parameter read tool with no output schema and no annotations, the description fully covers return values, success and error cases, cross-tenant behavior, and validity-window semantics. An agent has everything needed to call it correctly and interpret all possible responses.

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 itself fully documents the one parameter, including the charset, length, starting character, and case-sensitivity, so schema coverage is 100%. The description adds only 'by its id' and 'given to memory.put,' which is helpful but does not materially go beyond the schema.

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

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

The description opens with a specific verb and resource: 'Reads one memory item this tenant stored earlier with memory.put, by its id.' This accurately distinguishes it from the write sibling memory.put and from other tools: it is a read operation for a single memory item.

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 a clear use case: 'Use it to recall a fact, a setting or a note before acting on it; nothing is written.' It implies read vs. write by referencing memory.put, but it does not explicitly state 'use memory.put when storing' or list exclusions beyond that the call writes nothing.

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

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

With no annotations, the description carries full behavioral burden. It discloses that the call passes the policy gate, is recorded, returns a versionHash, and defines error responses for missing source, missing validUntilMs, and invalid id. It also implies mutation via 'writes' and 'replaces', though it doesn't explicitly state destructive effects beyond replacement.

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 few sentences, but every sentence adds meaningful information: the core action, usage rationale, recording and hashing behavior, and error cases. It is front-loaded with the primary action and does not waste 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 5 params, nested objects, no output schema, and no annotations, the description covers the essential operational details: what it does, how to use it, what it returns (example), and common errors. It doesn't explain the exact return structure beyond the example, but that is acceptable given no output schema and the example provided.

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 adds value by explaining the purpose of source and validUntilMs in the usage section and enumerating error responses tied to specific parameters (e.g., source-required, validUntilMs-required, id-invalid). This goes beyond the schema's basic field 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?

States a specific verb (writes/replaces) and resource (one memory item), with explicit scope (tenant, body's state directory on this machine). It also distinguishes from the sibling memory.get by saying 'for a later memory.get', making the action 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?

Provides clear context: use it to keep a fact for later retrieval, with provenance and validity window to avoid serving stale facts. It doesn't explicitly state when not to use it or name alternative tools, but the guidance is sufficient for an agent to decide when to write memory.

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

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

No annotations are provided, so the description carries the full burden. It discloses the read-only nature, that the call is recorded, and that an empty inbox returns [] – all beyond what the schema shows.

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 succinct, front-loads the core action (reads inbox), and includes necessary behavioral notes without 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?

Given zero parameters, no output schema, and no annotations, the description fully covers what an agent needs to know: what it does, when to use it, and the return format.

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

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

There are no parameters, so there is nothing to add. The schema coverage is 100%, and the description confirms no arguments are needed, which is sufficient.

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 the tenant's inbox and returns messages as a JSON array. However, it does not explicitly differentiate from sibling tools like message.send or memory.get, though the read-only nature is implied.

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 says to use it before deciding what to answer, which gives some context. But it does not mention when not to use it or compare with alternatives like memory.get.

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 disclosure burden, and it does so thoroughly: no network connection is opened, nothing leaves the body, the policy gate is passed, a signed decision record is left, and refusal/deferral outcomes are specified. This gives a complete behavioral picture.

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 dense but every sentence earns its place: core behavior, usage guidance, policy outcome, approval behavior, and return value. The most important disambiguation—queueing rather than delivering—is front-loaded.

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

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

Despite having no output schema and no annotations, the description fully specifies the return shape, error/refusal statuses, approval flow, and policy context. An agent has enough information to invoke this tool correctly and interpret its result.

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 the baseline is 3, but the description adds useful meaning: the host is lower-cased and checked against the egress allow-list, and the _ref interaction with operator approval and ref-reuse refusal is clarified. This goes beyond the schema without being redundant.

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: it 'queues one message in this tenant's outbox on this machine' and explicitly says it is not delivering the message. This clearly distinguishes it from message.read and from any actual network-send behavior the name 'send' might imply.

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 states when to use the tool ('Use it to hand off a message, not to deliver one') and points to the operator-run delivery step as the separate follow-up. It also explains policy approval/deferral behavior so the agent knows when the call will be queued versus held for an operator.

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 exist, so the description carries the full disclosure burden — and it excels: it reveals that 'authorized: true is a signed permission... not a transfer,' enumerates every refusal token (denied:spend-cap, denied:spend-payee, denied:spend-currency, denied:spend-daily, denied:spend-not-wired), explains the deferred:approval-required flow, and specifies the recorded result shape {authorized: true, ref, amountMinor, currency, payee, reference}. This far exceeds typical behavioral disclosure.

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

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

The description is a dense single paragraph, but every sentence earns its place: purpose and non-transfer caveat, when-to-use and policy checks, refusal modes, approval flow, and the not-wired fallback. It is front-loaded with the core purpose, though breaking the wall of text into shorter sentences would improve scannability.

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 no output schema and no annotations, the description must cover result states and does: every possible answer (denied tokens, deferred:approval-required:<ref>, allowed:<ref>) is specified, along with the recorded authorization object and the not-wired case. For a complex async approval tool, an agent has everything needed to invoke it correctly.

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

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

Schema description coverage is 100% — each parameter already has detailed descriptions including the policy constraints (amountMinor compared against cap and daily limit, currency must equal the policy currency, payee must be on the list, _ref reuse rules). The description reinforces how parameters map to refusal tokens but adds little beyond what the schema provides, so the high-coverage baseline of 3 applies.

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+resource — 'asks the body to authorize a payment and records the decision' — and immediately disambiguates by clarifying 'the body never moves money... not a transfer.' None of the sibling tools (memory.get, message.send, audit.explain) overlap with payment authorization, so an agent can identify this tool's role unmistakably.

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?

Gives explicit when-to-use guidance: 'Use it before any payment so that amount, currency, payee and reference are checked against the policy.' It also narrates the full acceptance/rejection flow and the approval path via 'verax approve, or the panel.' It stops short of explicitly naming alternatives or exclusions, though no sibling is a payment alternative, so 4 rather than 5.

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