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

With no annotations, the description carries the full disclosure burden and only says the export is complete and auditor-readable. It omits whether the operation is read-only, whether exports are size-limited or paginated, and whether sensitive data is included, leaving key behavioral traits unstated.

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 front-loaded sentence with no filler; the verb, resource, formats, and consumer are all stated immediately.

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

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

An output schema exists so return values need not be explained, and the single parameter is simple. However, for an export tool with no annotations, the description should say more about scope and operational limits to be 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?

The single format parameter has an enum of json/csv and a default, so the schema is largely self-explanatory despite 0% description coverage. The description confirms both formats exist but adds no detail on format-specific differences or defaults beyond what the schema shows.

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 ("Export the full logbook") plus the supported output formats, which distinguishes it from siblings like log_event and verify_logbook. It doesn't explicitly name what it is not, but the action is 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 auditor-facing framing implies when to use it (producing a human-readable record), but there is no explicit when-to-use or when-not-to-use guidance relative to verify_logbook or recent_events. The agent must infer the selection criteria.

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

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

With no annotations at all, the description carries the full behavioral burden and does disclose two non-obvious traits: arguments are stored with secrets masked, and the call returns the stored record including seq and hash. It does not say whether the log is append-only, whether entries can be amended or deleted, or what happens to orphaned "pending" rows, which matters for an audit 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?

Front-loaded verb+resource sentence, then a Who/What/Why/Approval/Outcome skeleton that maps directly onto the schema fields. Every line adds a distinct constraint or example; nothing is repeated from the title or padding.

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 12-parameter mutation tool with zero annotation coverage this is substantially complete: it explains the two-phase pending-then-outcome pattern, the approval taxonomy, secret masking and the returned identifiers, and an output schema exists so return values need no further prose. The remaining gap is the unexplained tags, run_id and result_summary fields plus no note on write permissions or log immutability.

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 has to compensate, and it does for most fields: agent_id is defined as the agent's stable name, model gets an example value, reason is constrained to one plain sentence, and approved_by/approval_rule are tied to their respective approval modes. Three parameters (tags, run_id, result_summary) get no explanation anywhere, which keeps this below a 5.

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?

"Record one agent action in the logbook" states a precise verb (record), a precisely scoped resource (one agent action) and the destination (logbook). It is immediately distinguishable from siblings verify_logbook, recent_events and export_logbook, which read, verify or export rather than append.

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 Outcome line gives real workflow guidance: log with "pending" before acting, then log the same action again with success/error/escalated. The Approval line similarly prescribes which approval mode pairs with which field. It never states when not to log, or why one would pick this over recent_events, 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?

No annotations are provided, so the description carries the full behavioral burden, yet it discloses almost nothing beyond the default count. It does not state the sort order (newest first?), whether results are truncated silently, whether it is read-only, or any permission or rate considerations; an output schema exists, which covers return shape but not runtime behavior.

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?

A single short sentence with the key noun and default front-loaded and no filler words. It is efficient, though its brevity edges toward under-specification rather than surplus wording.

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-optional-parameter read tool with an output schema, the description is close to adequate on shape but leaves real gaps: no ordering, no note about what happens when fewer than 'limit' events exist, and no signal at all about where this sits relative to its three siblings. With no annotations to fall back on, more context was needed.

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% for the single 'limit' parameter, so the description would need to compensate. It only restates the default value of 20, which the schema already declares via 'default': 20, and never explains what limit counts or how it interacts with the 'most recent' ordering.

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 ('Return the most recent events') with a scope qualifier ('most recent') and default count, so an agent knows it is a read of recent entries. It does not name or distinguish itself from the siblings log_event, verify_logbook, and export_logbook, leaving the differentiation implicit.

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?

'for a quick look' is the only usage guidance and is a vague intent hint rather than an explicit when-to-use rule. There is no statement about when to prefer export_logbook or verify_logbook instead, and no mention of prerequisites or ordering guarantees.

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 and does disclose a key behavior: it returns 'ok, event count and any problems in plain English', implying a non-mutating audit whose value is human-readable diagnostics. It omits other behavioral traits an agent needs, such as whether the call is read-only guaranteed, how expensive a full-chain scan is on a large logbook, or what happens on partial corruption.

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 short sentences with zero filler, the action and scope front-loaded and the result shape following immediately. Every clause 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?

An output schema exists, so the description need not explain return values, and with zero parameters there is little surface area to cover. The remaining gap is the absence of cost/scale or read-only context for a potentially full-logbook scan, which for a simple tool is minor.

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 there is nothing for the description to disambiguate beyond what the empty schema already conveys. The base score for a parameterless tool 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?

The description names a specific verb ('Check') and a precise resource and scope ('the whole logbook's hash chain'), which lets an agent distinguish this integrity check from the sibling writers/readers (log_event, recent_events, export_logbook) without opening any schema. It stops short of explicitly naming a sibling or contrasting scope, which keeps it from a 5.

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 only implied: the mention of checking the 'whole' chain suggests a full-integrity audit rather than an incremental read, but there is no explicit when-to-use, when-not-to-use, prerequisites or alternative-tool routing. An agent can infer the purpose but gets no decision rules.

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