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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses a real behavioral nuance: volume is estimated via Kibana's rule preview, which writes only to an isolated preview index and creates no real alerts. That directly clarifies the apparent tension between a 'write to an index' and a read-only tool, which is exactly the context the annotations cannot convey.

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 paragraphs: a front-loaded checklist of checks, then a focused note on how volume is estimated. Every sentence earns its place; only minor tightening of the second paragraph's wording would improve it.

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 needn't be explained, and the safety profile is well covered. However, for a tool with three parameters and zero schema descriptions, leaving lookback_hours and estimate_volume undefined is a meaningful gap 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 description coverage is 0%, so the description must carry parameter meaning, and it largely does not. It hints at volume estimation (mapping loosely to estimate_volume) and 'data is recent' (loosely to lookback_hours), but never defines rule_id, the lookback window's default/units, or what happens when estimate_volume is false.

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 gives a specific verb ('Check') plus a resource ('rule') and enumerates the exact conditions verified: source indices exist, data is recent, fields are populated, and projected volume is under the noise threshold. This reads clearly as a preflight/dry-run tool and is readily distinguishable from siblings like request_rule_enable or get_enable_request.

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

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

The use case (validating a rule before doing something else) is implied by 'will work here,' but the description never states explicitly that this should be run before request_rule_enable, nor does it say when it can be skipped. No alternative tool is named, so the agent must infer the workflow position.

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 and openWorldHint=false, so the safety profile is covered. The description adds the set of terminal and intermediate statuses (pending, approved, denied, enabled, failed, expired), which is genuinely useful behavioral context, but says nothing about whether statuses transition, how quickly, or what a caller should do on each.

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, front-loaded sentence with no filler; the parenthetical status list is the only added content and it earns its place. Slightly terse given what remains unexplained, but structurally clean.

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, return values need no explanation, and annotations cover the read-only nature. The remaining gap is the provenance and format of request_id plus the absence of any workflow guidance linking it to request_rule_enable, which matters for a one-parameter lookup 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 0% and the single parameter 'request_id' has no documentation in either schema or description. The description never explains where this ID comes from (presumably request_rule_enable) or what form it takes, so it fails to compensate for the coverage gap.

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 ('Get') and resource ('enable request') and enumerates the possible status values, so the agent knows exactly what is returned. It does not explicitly differentiate itself from siblings like request_rule_enable or list_rules, but the verb+resource combination is distinctive enough to infer the distinction.

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: an agent can infer this is the polling/lookup counterpart to request_rule_enable. There is no explicit statement of when to call it (e.g., after submitting an enable request) or when another sibling is the better choice.

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 and openWorldHint=false, so the safety profile is covered. The description adds which fields come back (ids, types, enabled state), which is useful context, but it says nothing about pagination behavior or result limits even though page and per_page exist — a notable omission for a list endpoint.

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 the core action front-loaded and zero filler. The return-fields clause is slightly redundant given the output schema, but it is compact and readable.

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 read tool with an output schema and read-only annotations, most of what an agent needs is present. The gaps are pagination semantics (page/per_page behavior, total counts) and whether the name search is fuzzy, which matter for calling it correctly on large rule sets.

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 carry the parameter burden. It clarifies that the string parameter is a name filter, but leaves page and per_page (with defaults 1 and 20) entirely unexplained, and does not say whether the search is exact-match or substring.

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 ("List detection rules") plus the optional name filter, which is enough to distinguish it from the sibling tools (check_rule_readiness, request_rule_enable, get_enable_request) that operate on individual rules. It does not explicitly name those siblings as alternatives, so it stops short of 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?

The parenthetical "optionally filtered by name" implies when to pass a filter, but there is no explicit statement of when to use this listing tool versus check_rule_readiness or request_rule_enable, and no prerequisites or exclusions are given. Usage is inferable rather than guided.

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 a non-read-only, idempotent, non-destructive mutation. The description adds real behavioral detail beyond that: it files a *pending* request rather than applying the change, it re-runs the readiness check as a side effect, and it refuses non-ready rules. It stops short of describing duplicate-request behavior or what the human approval flow looks like.

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 sentences, front-loaded with the action and immediately followed by the most important caveat ('This does NOT enable the rule'). No filler; the only mild redundancy is the restatement of 'enable a rule' in the negation, which is defensible as a guard against misuse.

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, return values need no explanation, and the mutation/refusal semantics are well covered. The remaining gap is the two undocumented required parameters, which for a request-submission tool is a meaningful omission since justification quality affects human approval.

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 two required parameters, so the description carries the full burden — and it adds nothing about them. Neither the expected form of 'rule_id' nor the purpose/audience of 'justification' (who reads it, why it matters) is explained anywhere.

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 ('Ask a human to enable a rule') and clarifies the critical scope boundary that it does NOT itself enable the rule. It implicitly separates itself from check_rule_readiness (which it re-runs internally) and get_enable_request, but never names those siblings explicitly.

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 context is clear: this is the path for requesting enablement and it is refused for rules not in 'ready' state. However, it never says what to do instead when a rule is refused (e.g., run check_rule_readiness first, or remediate readiness failures), nor does it name any alternative tool.

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