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

With read-only, idempotent, closed-world annotations already covering the safety profile, the description adds substantial behavioral context: the three view modes, pagination in `deployments`/`values`, and the distinction between `chart_source_url`, `source_urls`, `source_url`/`source_tag`, and `resolved_chart`. The caveat about confirming OCIRepository charts via `repo_clone` is unusually useful for correct invocation.

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 front-loaded with the core purpose, then structured around the `view` options and a targeted caveat. It is dense but largely purposeful; the final note is valuable, though the description is longer than strictly minimal.

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 the tool's complexity, the presence of an output schema, full schema coverage, and strong annotations, the description is complete enough for an agent to call it correctly. It covers the main view modes, pagination behavior, drill-down guidance, and the important chart-reference caveat.

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?

Although schema coverage is already 100%, the description adds real meaning beyond the schema by explaining what `view` modes do, how `repo` and `value_paths` narrow the `values` view, and that summary paths can be reused as `value_paths` including array forms. This helps the agent choose parameters correctly rather than merely restating 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?

The description gives a specific verb and resource: get details for one chart using a kubesearch.dev release id. It immediately disambiguates the id source by naming `search_releases` and gives an example id, so the agent can distinguish this from sibling search tools.

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 defines the three view modes, their defaults, and when to use each: start with `summary`, use `deployments` to find a repo, and use `values` as the drill-down. It also warns to prefer `summary` first, which is direct usage 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?

Annotations already declare readOnly/idempotent/closed-world, so the bar is lower; the description adds that matching is substring-based and scoped only to indexed releases' values, plus what comes back (key path, snippet, source file). It notes the kubesearch.dev /grep equivalence, useful for predicting result shape, though ranking/pagination behavior is left to the 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 tight sentences: what it greps, what it's good for with examples, what it returns. Nothing redundant and the core operation 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?

For a read-only search tool with full schema documentation, complete annotations, and an output schema covering return values, the description supplies everything else an agent needs: scope, match semantics, and intended use case.

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 `query`, `limit`, `offset`, and `case_sensitive` are all documented in-schema; the description's only added semantics is example query terms. Baseline 3 applies since the schema carries the parameter burden.

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 — full-text grep across the Helm `spec.values` of indexed HelmReleases/Applications — and pins the matching mode (substring). The scope is precise enough to separate it from search_releases and repo_grep without opening any 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 when-to-use guidance: finding real-world examples of a config key or value, with concrete query examples ('cert-manager.io', 'nodeSelector'). It does not name an alternative or exclusion (e.g. when to prefer search_releases or repo_grep), so it falls 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?

Annotations already provide idempotentHint=true and readOnlyHint=false. The description adds valuable lifecycle context: clones are temporary, have a TTL, and are auto-deleted. This goes beyond annotations to explain why the tool is optional, and does not contradict destructiveHint=false since the clone is temporary.

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, front-loaded with the action ('Delete a temporary clone'), and both sentences serve a purpose: the first states the action and rationale, the second clarifies optionality. No wasted 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 single-parameter tool with an output schema and strong annotations, the description covers the purpose, usage context, and lifecycle behavior (TTL, auto-deletion). It is fully sufficient for an agent to decide when and why to invoke it.

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% with the parameter 'handle' described as 'The clone handle from repo_clone.' The tool description merely references this relationship without adding new meaning, so the schema carries the full semantic burden.

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 the verb 'Delete' with a specific resource ('temporary clone created by repo_clone') and clearly distinguishes this from sibling tools like repo_clone, which creates clones. The qualifier 'temporary' adds necessary scope.

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 it (to free disk before TTL) and when not to (since clones auto-delete after inactivity, making it optional). The alternative is effectively doing nothing, which the description implies by calling it 'polite'.

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?

The description discloses substantial behavioral details beyond the annotations: the clone is shallow, sandboxed, size/time-limited, auto-deleted after a TTL, resolves indexed names to real clone URLs and branches, and requires eventual cleanup. This is exactly the kind of context an agent needs for a stateful, non-read-only 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?

The description is front-loaded with the core purpose, then adds precise operational details in compact sentences. Every sentence earns its place, covering input format, clone behavior, return value, companion functions, and cleanup without 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?

The description is complete for a tool with one parameter, meaningful annotations, and an output schema. It explains what the caller receives, how the temporary resource is governed, and what follow-up actions are expected. Nothing essential for correct invocation 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?

With 100% schema description coverage, the schema already documents the `repo` parameter, and the description adds meaningful extra context: it gives an example, explains that indexed names are resolved to the real clone URL and branch, and states which URL forms are accepted. 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: temporarily clone a public Git repository to review actual files. It clearly distinguishes itself from siblings by explaining that it returns a handle consumed by repo_list_files, repo_read_file, and repo_grep, and that repo_cleanup should be called afterward.

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 clearly conveys when to use the tool: when actual repository files need to be inspected, rather than relying only on metadata. It also names the companion tools and cleanup routine, but it does not explicitly state when not to use it or contrast it directly with the kubesearch_* 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?

Annotations already signal readOnly, idempotent, and closed-world behavior. The description adds valuable behavioral details: search scope ('text contents'), optional glob filtering, return format ('file paths, line numbers, and matching lines'), and truncation handling. This goes beyond annotation basics and helps the agent predict tool output.

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, all informative. The first sentence captures the core action, the second adds an optional parameter, and the third provides practical usage advice. No filler or repetition; front-loaded and efficient.

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 search tool with output schema and rich annotations, the description covers key contextual aspects: prerequisite (cloned repository), optional filter, return format, and behavior on truncation. It doesn't mention case_sensitive or limit explicitly, but the schema fully documents those, and the truncation guidance substitutes for deeper pagination details.

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%, with each parameter including a description, so the baseline is 3. The description does not significantly expand on parameter meaning beyond what the schema provides—it only restates 'by handle' and 'glob' in narrative form. No new parameter-level insight is added.

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 specific verb ('Search') and a specific resource ('text contents of a previously cloned repository'), immediately distinguishing it from sibling tools like repo_list_files (list files) and repo_read_file (read one file). It also specifies the output (file paths, line numbers, matching lines), making the tool's purpose 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 description implies the prerequisite of a prior repo_clone operation via 'previously cloned repository (by handle)', and offers explicit guidance for handling truncated results: 'narrow the search with a longer query or a glob rather than paging.' It does not explicitly mention when to use this over kubesearch_grep_values, but given sibling list and context, the usage 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?

Annotations already mark it read-only, idempotent and closed-world; the description adds behavior annotations can't capture — hits grouped by repo with most-starred first, per-group `handle` for follow-ups, and the crucial caveat that while `pool.syncing` is true an empty result is not final and should be retried.

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, front-loaded with purpose, then result shaping, then the sync caveat in priority order. The first sentence is long with an em-dash aside, but every clause carries information an agent needs.

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?

Covers scope, result grouping, follow-up handles, and the warm-up/retry condition — the main failure mode an agent would otherwise misread as 'no matches'. Return-value detail is covered by the output schema, so nothing required for a correct call 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 query/glob/limit/max_per_repo/case_sensitive are already documented in the schema. The description adds no per-parameter syntax or defaults beyond that; the only extra detail is about the `pool` output field, not the inputs.

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: substring-search the files of top indexed home-ops repos without cloning. It explicitly distinguishes itself from `grep_values` by scope ('every resource kind ... not just Helm values'), so an agent can pick between the two 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?

Gives clear usage context ('no clone step needed', all resource kinds) and names the follow-up tools `repo_read_file` / `repo_list_files` / `repo_grep` for drilling into a hit. It does not explicitly state when to prefer the single-repo `repo_grep` sibling over this pool-wide search, leaving one routing decision implicit.

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 and idempotentHint, covering the safety profile. The description adds useful behavioral context beyond annotations: the handle must come from repo_clone, and listing can be scoped via sub-path and glob. No contradictions.

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, front-loaded with the core purpose, followed by optional parameters and a necessary prerequisite. Every phrase earns its place with no 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 simple list files tool with an output schema, the description covers the prerequisite (handle from repo_clone) and options (path, glob). It does not explicitly state whether the listing is recursive, but the glob pattern '**/*.yaml' implies recursive behavior, and the output schema likely clarifies return structure. No major gaps.

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%, with each parameter (handle, path, glob) fully described in the input schema. The description restates these options but adds no new semantic detail beyond examples already present in the schema, so 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?

The description clearly states a specific action and resource: 'List files in a previously cloned repository (by handle)'. This distinguishes it from sibling tools like repo_read_file and repo_grep, which operate on file contents. The optional path and glob filters are additional specificity.

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 prerequisite via 'Use the handle returned by repo_clone' and explains optional scoping/filtering with path and glob. It does not explicitly name alternatives or when-not-to-use conditions, but the context is strong enough for an agent to understand when this tool applies.

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 read-only and idempotent hints. The description adds behavioral details about binary files being refused and large files being truncated, which goes beyond the structured annotations.

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, front-loaded with the action, and each sentence earns its place without unnecessary elaboration.

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 a rich output schema and good annotations, the description covers the key prerequisites and constraints (prerequisite handle, binary refusal, truncation) sufficiently for an agent to use 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?

The input schema covers 100% of parameters with descriptions. The description reinforces the handle's origin but doesn't add significant new semantic information beyond what the schema already provides.

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 a text file from a cloned repository using a handle and relative path. It also mentions binary refusal and truncation, which distinguishes it from sibling tools like repo_list_files and repo_grep.

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: it works on previously cloned repos and instructs to use the handle from repo_clone. It doesn't explicitly name alternatives, but the usage context is unambiguous.

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 and idempotentHint, so the safety profile is covered. The description adds genuinely new behavior: case-insensitive substring matching, the upstream data source (public home-ops clusters), the ranked-by-usage result ordering, and what each result row contains, which is more than the annotations 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 sentences, front-loaded with the verb and resource, then the matching semantics and return shape. Nothing is padded and no sentence restates the tool name.

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, the description needn't explain return values, yet it does so briefly and accurately. For a three-parameter read-only search it covers everything an agent needs to invoke it; only sibling routing is absent.

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 three parameters are already documented, giving a baseline of 3. The description only adds the case-insensitivity of the substring match and the fact that results are ranked by usage count, which is marginal value 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 names a specific verb (Search) and a precise resource (container image repositories on kubesearch.dev), plus the matching rule (case-insensitive substring on repository). It clearly reads as a distinct resource domain from the sibling repo_* and search_releases tools, though it never names an alternative to route against.

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 implied by "used across public home-ops clusters" and the note that it is equivalent to the kubesearch.dev /image search. However, there is no explicit when-to-use / when-not guidance and no mention of how this differs from search_releases or repo_grep_all for an agent choosing between them.

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?

Beyond the readOnly/idempotent annotations, the description discloses result ordering (grouped by chart source, ranked by repo deployment counts), the identity/pagination contract via `id`, and an important normalization caveat about chart_source_url collapsing registries with source_urls and resolved_chart for the real chart. That is substantial behavioral context an agent could not infer from annotations.

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 purpose and routing to get_release are front-loaded in sentence one, and the grouped/ranked behavior follows logically. The second paragraph is dense and clause-heavy, but each clause carries real information about normalization that would otherwise mislead.

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 three-parameter read-only search with a full output schema, the description adds everything an agent needs: matching semantics, result grouping and ranking, the id-to-get_release handoff, and the normalization traps in chart_source_url/source_urls. No material gap remains.

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 limit and offset are already documented, and the description largely reinforces query semantics rather than extending them. It adds the useful note that the returned `id` feeds get_release, but does not clarify pagination behavior or substring edge cases beyond the schema 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?

First sentence gives a specific verb (search), a concrete resource (kubesearch.dev Flux HelmReleases / Argo Applications), and matching semantics (substring, case-insensitive) that distinguish it from siblings like get_release and search_images. It also names the follow-up tool for full details.

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 states the tool mirrors the kubesearch.dev homepage search, gives a concrete example query ('cert-manager'), and routes the agent to get_release for full details. It stops short of explicit when-not-to-use guidance against sibling search tools, but usage conditions are clear.

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?

The annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false. The description adds useful behavioral context by specifying that the data is locally cached and by enumerating the freshness and size details reported, though it does not discuss auth or rate limits.

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, front-loaded with the core action and followed by a clear usage cue. Every phrase adds information about the report contents or purpose.

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-argument status tool with an output schema and annotations covering safety, the description is complete enough: it says what is reported and why an agent would call it. Return values are handled by the output 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?

The tool takes zero parameters, so per the baseline rule the schema cannot be improved by parameter description. The description appropriately focuses on the reported output rather than input 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?

The description states a specific verb and resource: reporting freshness and size of locally cached kubesearch.dev data. It enumerates the exact fields returned, making the tool's purpose clear, though it does not explicitly differentiate itself from the sibling search/repo tools.

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 a clear use case: confirming how current the search data is. It does not list when not to use it or name alternatives, but the context is sufficient for a status tool with no obvious sibling alternative.

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