mulewatch

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

No annotations are provided, so the description carries the full burden, and it does disclose meaningful traits: the logs are live-tail (not archived, implying ephemeral/non-historical data) and the response is an analysis-ready aggregate rather than raw entries. It still omits the read-only safety profile, permission requirements, and any latency or streaming caveats around live-tail fetching.

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 sentences with zero filler; the capability and payload shape come first, then the routing preference. Nothing is repeated from the schema and 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?

With no output schema, the description usefully characterizes the return payload, and the rich parameter schema covers input details. It is nearly complete for a read tool of this complexity, though pagination/offset behavior on a live-tail stream and failure modes when no target is reachable are left unstated.

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% across 16 parameters, including defaults, ranges and enum values, so the schema already documents parameter meaning thoroughly. The description adds only indirect context (the priority/logger/instance fields that searchTerms match against), 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?

States a specific verb and resource ('Fetch live-tail logs for a Mule application') and goes further by naming the shape of the returned payload (normalized lines plus counts by priority, logger and instance). It explicitly distinguishes itself from the sibling anypoint_list_app_logs, so an agent can route without opening either schema.

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 selection rule: 'Prefer this over anypoint_list_app_logs when diagnosing a problem.' It names the alternative and the condition that favors this tool. It stops short of stating when the sibling is the better choice (e.g., raw paginated log listing), so it is not fully bidirectional 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 supplied, so the description carries the full behavioral burden. It usefully discloses what comes back (assets, endpoints, technology) and, via the includeRaw parameter, that normalized fields are the default. However, it says nothing about pagination semantics, permission/credential requirements, or rate limits for what is implicitly a read-only list operation.

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 that names the operation, the scope, and the return payload with 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?

For a read-only list tool with no annotations and no output schema, the description does the essential work of stating what is listed and roughly what is returned. It is nearly complete; pagination and environment-selection nuance are covered by the rich schema, so only minor context 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 eight parameters including defaults, filtering, and the environmentId/environmentName exclusivity. The description adds nothing about parameter behavior, so the 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 (List) and a precisely bounded resource (API instances managed by Anypoint API Manager), plus the scope (an environment) and the payload returned (assets, endpoints, technology). It is naturally distinct from siblings like anypoint_list_deployed_apps and anypoint_list_environments, though it never explicitly contrasts itself with 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 phrase 'in an environment' hints that environment scoping matters, but there is no explicit when-to-use guidance, no prerequisites, and no mention of when a caller should reach for this tool versus anypoint_list_deployed_apps or anypoint_search_exchange_assets. An agent gets no routing help from the text.

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 it does disclose the most consequential behavioral trait: results come from a bounded rolling buffer rather than full history. It omits other traits the agent would want — read-only nature (only implied by 'List'), rate/volume limits, and how the 'auto' target fallback behaves — but the buffer caveat is the key gotcha and it is stated plainly.

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 sentences with zero filler; the scope limitation is front-loaded and the alternative is appended as the resolution. Nothing redundant with the name or title.

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 14-parameter tool with no annotations and no output schema, the description covers the essential conceptual gap (live tail vs. archive) but says nothing about output shape, pagination across offset/limit, or the behavior of the auto target fallback and includeErrors flag. Adequate, though an agent still infers a fair amount from the schema alone.

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% across all 14 parameters, so the schema already explains limit, offset, target, time filters, environment resolution, and the rest. The description adds no parameter-level detail beyond what the schema provides, which is the expected baseline when the schema does the heavy lifting.

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 the latest Runtime Manager logs for a Mule application') and immediately bounds what 'logs' means here. It also names the sibling it is not (anypoint_search_archived_logs), so an agent can distinguish it from anypoint_get_app_logs_for_analysis and the archived-log tool without opening schemas.

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 defines the operating window ('live tail only — a small rolling buffer') and states the exclusion condition plus the named alternative: 'For anything older than the buffer, use anypoint_search_archived_logs.' That is a direct when-to-use/when-not-to-use routing rule.

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 does disclose a meaningful domain behavior (environments live on business groups, not the root organization) and that ids are returned, but it says nothing about auth/permission requirements, pagination, or the size/shape of the result set.

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 tightly written sentences with zero filler; the core purpose comes first and the fallback routing follows. 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?

For a single-optional-param, annotation-free read tool with no output schema, the description covers purpose, scope, defaulting behavior, and cross-tool routing. Remaining gaps (result size, pagination, permission needs) are minor given the tool's simplicity.

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 there is only one optional parameter (rootOrgId), whose default behavior is already documented in the schema. The description adds no syntax or format detail beyond the schema, so the 3 baseline 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 ('List the business groups') and scope ('under the credentials' organization'), plus notes the returned ids. It also implicitly separates itself from anypoint_list_environments by explaining that environments hang off business groups rather than the root org.

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 an explicit conditional directive: 'call this first if anypoint_list_environments returns nothing,' naming the sibling tool and the failure condition that should route the agent here. This is exactly the when/when-alternative guidance the dimension asks for.

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. It usefully discloses that the tool federates across Application Manager, legacy CloudHub, and hybrid targets, which is real behavioral context not available in the schema, but it is silent on read-only nature, permission requirements, and empty-result 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 front-loaded sentence that names the resource first and then qualifies scope; every clause carries information and there is 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?

For a 7-parameter list tool with no output schema and full schema coverage, the description is nearly complete. The only gap is the absence of any hint about the shape of the normalized results, which the schema cannot supply.

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 every parameter (limit, target, orgId, environmentId/environmentName, includeRaw, includeErrors) is already documented. The description echoes the environment scoping and target variety but adds no syntax or precedence detail beyond the schema's baseline.

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 (List) and resource (deployed Mule applications), and scopes them to an environment across three target families. It does not name or contrast any sibling tool, so an agent must infer how it differs from anypoint_list_app_logs or anypoint_list_environments.

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?

There is no when-to-use guidance, no exclusions, and no alternative tools mentioned. The phrase 'in an environment' hints that an environment parameter is expected, but the description never states the condition that selects this tool over its siblings.

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 disclosure burden, and it does add real behavior: output may be filtered by the ANYPOINT_ALLOWED_ENVIRONMENTS setting, and an empty result has a specific diagnostic meaning (root org) rather than 'no data'. It still omits pagination and permission/auth requirements, so it is not exhaustive.

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 tight sentences, front-loaded with the core action, followed by the empty-result remedy and the filtering caveat. No filler and nothing redundant.

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 optional-parameter list tool with no output schema, the description covers the action, the result caveat, the fallback path, and the filtering constraint. An agent has everything needed to call it correctly and interpret an empty response.

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 schema already documents the orgId default chain (ANYPOINT_ORG_ID, then credentials' organization). The description only echoes the 'business group' framing and adds the root-org troubleshooting hint, so it does not meaningfully extend parameter meaning 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?

States a specific verb and resource with scope: 'List the Anypoint environments in a business group.' That is concrete enough for an agent to act on immediately. It does not explicitly contrast itself with the sibling listing tools, though it does route to anypoint_list_business_groups for a specific failure mode.

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 an explicit conditional path: if the call returns nothing, the orgId is likely the root organization and the agent should call anypoint_list_business_groups instead. It also flags that results are restricted when ANYPOINT_ALLOWED_ENVIRONMENTS is set, which tells the agent when a partial list is expected rather than a bug.

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 usefully discloses the enabling prerequisite, but says nothing about read-only nature, authorization failures when Monitoring is disabled, throttling, or the archive-file download/parse cost implied by maxFiles/maxEntities. Prerequisite disclosure is real added value, but the behavioral picture is incomplete.

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 API/purpose leads, the prerequisite follows, and the use case closes. Nothing is repeated from the schema.

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 tool with no output schema and no annotations, the description covers purpose, scope boundary, prerequisite, and intended use case adequately. It could do slightly more on fallback behavior (full-scan replica probing) and return shape, but the essential calling 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 100% and every parameter (date range, limit, maxFiles, maxEntities, errorOnly, environment resolution) is already documented in the schema. The description adds no parameter-level meaning beyond it, so the baseline 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 (search) and resource (historical Mule application logs) and names the underlying API. It also distinguishes itself from sibling log tools by scope ('dates beyond the live tail's rolling buffer'), so an agent can separate it from anypoint_list_app_logs without opening a schema.

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 clear context ('for dates beyond the live tail's rolling buffer', 'past-date incident investigation') and states a prerequisite (Anypoint Monitoring enabled). It doesn't explicitly name the sibling to use for live/near-real-time logs, leaving that routing to inference, which keeps it 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 burden of behavioral disclosure, and it says nothing about read-only safety, authentication/organization scoping, or rate limits. It also adds no return-shape or pagination behavior beyond what the schema already documents for limit/offset. The implicit read-only nature of 'search' is the only signal.

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 efficient sentence with the verb and resource front-loaded and the covered asset types listed as a scannable clause. Nothing is wasted, though the sentence is short enough that it leaves obvious gaps unfilled rather than being maximally 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?

With six optional parameters, 100% schema coverage, and no output schema, the description is adequate but minimal. It does not describe what the returned assets look like or how search interacts with the types filter, so an agent gets no help on result interpretation beyond the 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 description coverage is 100%, so all six parameters are already documented in the schema (limit, orgId, types, offset, search, includeRaw). The description reinforces the types filter by naming asset kinds, but adds no format or syntax detail beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 (Search) and resource (Anypoint Exchange assets), and enumerates the asset kinds covered (APIs, connectors, templates, examples, fragments). It is instantly distinguishable from the sibling tools, which all target different resources (environments, apps, logs, business groups). No explicit sibling routing is needed because none of them overlap.

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?

There is no explicit when-to-use guidance, no prerequisites, and no mention of alternatives or when not to use it. That you would call it to find assets is only implied by the verb. For a search tool this leaves the agent to infer scoping and pagination strategy on its own.

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 it does distinguish itself as a verification/inspection read rather than a mutation and frames itself as a troubleshooting entry point. It omits whether verification fails hard on bad credentials and what the output looks like, which is a minor gap given zero parameters.

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 tightly written sentences with no filler. The identity/verification purpose comes first and the troubleshooting cue is placed last as the actionable instruction.

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?

Although there is no output schema, the description enumerates the fields it surfaces (business group, host, environment allowlist), which is enough for an agent to know what it gets back. Only the failure semantics of a bad-credential check are unstated.

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 no parameters, so there is nothing to disambiguate; baseline is 4. The description correctly indicates the results are derived from server-side configuration rather than caller-supplied input.

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 pairs specific verbs (verify, show) with concrete resources (Anypoint credentials, business group, host, environment allowlist), going well beyond the name 'whoami'. It is clearly a diagnostic/identity tool, which cleanly separates it from the list_* 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?

It gives an explicit triggering condition: 'Use this first when a call fails.' That is real when-to-use guidance. It stops short of naming alternatives or stating when not to use it, but no sibling serves the same diagnostic purpose.

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