Search Shakespeare monologues, plays, paraphrases and summaries from shakespeare-monologues.org
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Average 3.6/5 across 9 of 9 tools scored.
Each tool serves a distinct purpose: retrieval by ID, daily feature, paraphrased version, play/scene summaries, character listing, play listing, random selection, and search. No overlapping functions.
All tools follow a consistent verb_noun pattern using snake_case (e.g., get_monologue, list_plays, search_monologues). Naming is clear and predictable across the set.
9 tools is appropriate for a focused domain like Shakespeare monologues. It covers retrieval, browsing, search, and supplementary features without being overwhelming.
The tool set covers core read operations well (get by ID, search, random, by character, play summaries). A minor gap is the lack of a direct 'list monologues by play' tool, but search can approximate it.
get_monologueBInspectFetch one monologue's catalogue entry by its numeric id. Follow the returned url for the full text.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | The monologue's numeric id (from search_monologues). | |
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." | |
| monologue_id | No | Deprecated alias for `id`. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only mentions that the tool returns a catalogue entry and the user should follow the url for full text. It does not disclose behavioral traits like error handling, read-only nature, or performance implications.
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 purpose, and provides a clear follow-up instruction. No unnecessary 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?
Given the lack of output schema and only three parameters, the description is adequate but could be more complete. It mentions the returned url but does not describe other fields in the catalogue entry.
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 baseline is 3. The description reinforces the use of 'id' but does not add extra semantics beyond what the schema already provides. The context parameter is not mentioned in the description.
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 'Fetch one monologue's catalogue entry by its numeric id', specifying the verb and resource, and distinguishes from siblings like get_monologue_of_the_day or random_monologue.
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 does not provide guidance on when to use this tool versus alternatives like search_monologues or get_paraphrased_monologue. No context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_monologue_of_the_dayBInspectThe current 'Monologue of the Day' — the piece most recently posted to the site's social feeds.
| Name | Required | Description | Default |
|---|---|---|---|
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description fails to disclose behavioral traits such as read-only nature, authentication needs, or rate limits. It only hints at recency but lacks substantive behavioral context.
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 single, concise sentence with no unnecessary words. It is front-loaded and efficiently communicates the tool's function.
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 sibling tools like get_monologue, the description could better specify return format or content. However, for a simple retrieval tool, the basic purpose is conveyed.
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 a single parameter 'context' already described in detail. The description adds no additional meaning beyond the schema, meeting the baseline for high coverage.
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 identifies the tool as retrieving the most recently posted monologue to social feeds, distinguishing it from sibling tools like get_monologue and random_monologue. However, it lacks an explicit verb like 'retrieve' or 'fetch'.
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?
No guidance is provided on when to use this tool versus alternatives such as get_monologue or random_monologue. The description does not mention when not to use it or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_paraphrased_monologueAInspectFetch a monologue's full text alongside its modern-English, line-by-line paraphrase. The paraphrase is AI-generated (Claude) and may be null if it hasn't been generated yet — the url always has the monologue itself.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | The monologue's numeric id (from search_monologues). | |
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." | |
| monologue_id | No | Deprecated alias for `id`. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description fully bears the responsibility. It discloses that the paraphrase is AI-generated (Claude) and may be null, and that the URL always contains the original monologue. This is adequate for a simple fetch operation, though no mention of read-only or side effects.
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, 36 words total, with no wasted verbiage. The action and key details (paraphrase origin, null possibility) are 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?
Given no output schema, the description covers the essential behavior: fetch original text + paraphrase, with AI generation disclosure. The deprecated parameter is noted in schema. It lacks details on response structure but is sufficient for this simple fetch 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 100%, so the baseline is 3. The description does not add extra meaning to the parameters beyond what the schema already provides; it only gives context about the return value. Baseline score 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 uses a specific verb ('Fetch') and identifies the exact resources ('monologue's full text' and 'modern-English, line-by-line paraphrase'). It clearly differentiates from sibling tools like 'get_monologue' (which likely returns only original text) by specifying the inclusion of the paraphrase.
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?
While the description implies use when a paraphrase is needed, it does not explicitly state when to use this tool versus 'get_monologue' or other siblings. No 'when-not' or alternative names are given, but context is reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_play_summaryAInspectFetch an AI-generated summary of a play (e.g. 'Hamlet', 'The Tempest'). May be null if not generated yet.
| Name | Required | Description | Default |
|---|---|---|---|
| play | Yes | Play title (exact or partial). | |
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description only discloses that the summary 'May be null if not generated yet'. It does not mention any other behavioral traits such as permissions, latency, or side effects.
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 single sentence that efficiently conveys the tool's purpose and a key behavioral note with 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?
Given the tool's simplicity and lack of output schema, the description is adequate but does not explain what the summary contains or any usage constraints beyond nullability.
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. The description adds no additional meaning beyond what the schema provides for the 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 clearly states the verb 'Fetch' and the resource 'AI-generated summary of a play' with examples, distinguishing it from siblings like get_monologue and get_scene_summary.
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 mentions that the summary may be null if not generated yet, giving context but no explicit guidelines on when to use this tool over alternatives like get_scene_summary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_scene_summaryAInspectFetch an AI-generated summary of the scene a monologue appears in (context for the speech). May be null if not generated yet.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | The monologue's numeric id (from search_monologues). | |
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." | |
| monologue_id | No | Deprecated alias for `id`. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It discloses the possibility of null return but omits other behavioral traits such as whether it is a read-only operation (likely, but not stated), authentication requirements, or rate limits. This is insufficient for a fetch 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 a single, well-structured sentence of 19 words. It front-loads the action and conveys essential information with no redundancy or unnecessary details.
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 simplicity (fetches one piece of information, no output schema), the description is mostly complete: it explains the output (summary, possibly null) and the input (monologue context). However, it could be more explicit about the return value structure beyond 'summary'.
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 clear parameter descriptions in the schema. The tool description does not add additional meaning beyond what the schema already provides, so baseline score of 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 the action ('Fetch an AI-generated summary'), the target resource ('the scene a monologue appears in'), and its purpose ('context for the speech'). It distinguishes from sibling tools like get_monologue (monologue text) and get_play_summary (play-level summary).
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 usage context by stating the summary is for speech context, and mentions it may be null if not generated. However, it does not explicitly contrast with alternatives (e.g., when to use get_scene_summary vs get_play_summary) or provide prerequisites like 'monologue_id must come from search_monologues'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_all_monologues_for_a_characterAInspectList every monologue spoken by a given character (e.g. 'Hamlet', 'Rosalind'). Matches the character name exactly first, then as a substring.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 50). | |
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." | |
| character | Yes | Character name. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description provides a key behavioral detail: matching character name exactly first then as substring. This adds value beyond the schema. However, it does not describe output format or pagination behavior, missing some transparency.
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 single sentence that efficiently conveys the purpose, examples, and matching behavior. 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?
The description covers the core function and matching strategy, but without an output schema, it fails to inform the agent about the return structure (e.g., monologue IDs, texts). This is a gap for a listing tool with no 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?
Schema coverage is 100%, baseline 3. The description adds context for the 'character' parameter (matching strategy) but adds nothing for 'context' or 'limit'. This provides some added meaning but not significant improvement.
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 lists all monologues for a given character, with an example and matching strategy. It distinguishes from siblings like search_monologues (which searches by content) and get_monologue (single monologue).
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 when to use this tool (when you need all monologues for a character) but does not explicitly state when not to use it or compare with alternatives. The context of sibling tools helps but is not leveraged in the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_playsAInspectList Shakespeare's plays with their classification (Comedy/History/Tragedy) and monologue counts.
| Name | Required | Description | Default |
|---|---|---|---|
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries burden. It describes what is returned but doesn't disclose ordering, pagination, or the required 'context' parameter's role beyond 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?
One sentence, front-loaded with action and resource, 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 simple list tool with 1 parameter and no output schema, the description sufficiently covers the output structure (classification, monologue counts) and purpose.
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 a detailed description for the only parameter. Description adds no additional parameter semantics beyond what schema 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?
Description clearly states the verb 'List', the resource 'Shakespeare's plays', and specifies the information returned (classification and monologue counts). It distinguishes from siblings like get_play_summary.
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?
No explicit guidance on when to use vs alternatives. The name and description imply it's for listing all plays, but no exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_monologueAInspectReturn one random monologue, with optional gender/play filters. Useful for a suggestion when the user is undecided.
| Name | Required | Description | Default |
|---|---|---|---|
| play | No | Exact or partial play title. | |
| gender | No | Role gender: Men, Women, or Both. Natural words like 'male'/'female' are accepted. 'Men'/'Women' also include gender-neutral ('Both') roles. | |
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It only states the core function without disclosing side effects, output format, or any constraints beyond filters. Minimal behavioral context.
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, no extraneous information. The purpose is front-loaded and clear.
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 no output schema and simple operation, the description is adequate. It explains the tool's role among siblings but omits return format, which is acceptable for a random selection 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 coverage is 100%, so baseline is 3. The description adds minimal value beyond 'optional gender/play filters', which is already implied by the schema. No further detail on parameter formats or usage.
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 it returns a random monologue with optional gender/play filters, which is a specific verb-resource combination. It distinguishes itself from siblings like get_monologue and search_monologues by emphasizing randomness and suggestion use.
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 'Useful for a suggestion when the user is undecided,' indicating when to use it. However, it does not mention when not to use or specify alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_monologuesAInspectSearch Shakespeare monologues by free text (matches character, play, or first line) plus optional filters. Returns matches, each with a permalink url.
| Name | Required | Description | Default |
|---|---|---|---|
| act | No | Filter to a specific act number. | |
| play | No | Exact or partial play title. | |
| limit | No | Max results to return (default 25). | |
| query | No | Free text — matched against character name, play title, and first line. | |
| style | No | Verse or prose. | |
| gender | No | Role gender: Men, Women, or Both. Natural words like 'male'/'female' are accepted. 'Men'/'Women' also include gender-neutral ('Both') roles. | |
| context | Yes | Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization." |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that results include a permalink url but omits details on behavior for empty results, pagination beyond the limit, or ordering. For a search tool, this is moderate but not comprehensive.
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-loading the core purpose and method. Every sentence adds value with no redundancy or excessive length. It is optimally concise.
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 7 parameters and no output schema, the description covers the basic function and return format. However, it lacks details on search semantics (e.g., case sensitivity, stemming, combination of filters). This is adequate but leaves room for ambiguity.
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 the description adds little beyond stating 'plus optional filters'. The schema already documents each parameter well. The description does not significantly augment parameter meaning, earning a baseline score of 3.
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 verb 'Search', the resource 'Shakespeare monologues', and the search method 'free text (matches character, play, or first line)'. It also mentions optional filters and the return format (matches with permalink url). This distinguishes it from siblings like get_monologue (specific ID) and random_monologue (random selection).
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 lacks explicit guidance on when to use this tool versus alternatives. It does not specify when filters should be applied or when to prefer this search over fetching a specific monologue. Sibling tools are listed but no comparative context is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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