Shakespeare's Monologues

search_monologues

Read-only

Search Shakespeare monologues by free text (matches character, play, or first line) plus optional filters. Returns matches, each with a permalink url.

Input Schema

Name	Required	Description
`act`	No	Filter to a specific act number.
`play`	No	Exact or partial play title.
`limit`	No	Max results to return (default 25, max 100).
`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 in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`conversation_id`	No	Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedOct 11, 2026

changedInput schema / properties / context / description

Previous value: -"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.\""New value: +"Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""

addedInput schema / properties / conversation_id

Added value: +{
+  "description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.",
+  "type": "string"
+}

addedInput schema / properties / llm_model

Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}

changedInput schema / required

Previous value: -[
-  "context"
-]New value: +[
+  "context",
+  "llm_model"
+]

Changed6 schema fields changedOct 3, 2026

changedInput schema / properties / act / type

Previous value: -[
-  "number",
-  "string"
-]New value: +[
+  "number",
+  "string",
+  "null"
+]

changedInput schema / properties / gender / type

Previous value: -"string"New value: +[
+  "string",
+  "null"
+]

changedInput schema / properties / limit / type

Previous value: -[
-  "number",
-  "string"
-]New value: +[
+  "number",
+  "string",
+  "null"
+]

changedInput schema / properties / play / type

Previous value: -"string"New value: +[
+  "string",
+  "null"
+]

changedInput schema / properties / query / type

Previous value: -"string"New value: +[
+  "string",
+  "null"
+]

changedInput schema / properties / style / type

Previous value: -"string"New value: +[
+  "string",
+  "null"
+]

Changed8 schema fields changedOct 3, 2026

changedInput schema / properties / act / type

Previous value: -"integer"New value: +[
+  "number",
+  "string"
+]

removedInput schema / properties / gender / enum

Removed value: -[
-  "Men",
-  "Women",
-  "Both"
-]

changedInput schema / properties / limit / description

Previous value: -"Max results to return (default 25)."New value: +"Max results to return (default 25, max 100)."

removedInput schema / properties / limit / maximum
```
Removed value: -100
```
removedInput schema / properties / limit / minimum
```
Removed value: -1
```

changedInput schema / properties / limit / type

Previous value: -"integer"New value: +[
+  "number",
+  "string"
+]

changedInput schema / properties / style / description

Previous value: -"Verse or prose."New value: +"Verse or Prose."

removedInput schema / properties / style / enum
```
Removed value: -[
-  "Verse",
-  "Prose"
-]
```

Changed1 schema field changedJul 27, 2026

changedInput schema / properties / gender / description

Previous value: -"Role gender as catalogued. 'Men'/'Women' also include gender-neutral ('Both') roles."New value: +"Role gender: Men, Women, or Both. Natural words like 'male'/'female' are accepted. 'Men'/'Women' also include gender-neutral ('Both') roles."

Changed3 schema fields changedJul 21, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

addedInput schema / properties / context

Added value: +{
+  "description": "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.\"",
+  "type": "string"
+}

addedInput schema / required
```
Added value: +[
+  "context"
+]
```

First observedJul 19, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description still adds non-redundant behavior: it discloses the shape of the return payload (matches, each with a permalink `url`), which is the only place an agent learns this since there is no output schema. It says nothing about pagination limits or the conversation_id handshake, but the core behavioral disclosure is present.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences with the core capability front-loaded and the return-format note second. No filler, no restatement of the title or name, and every clause carries information.

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

Completeness4/5

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

For a nine-parameter search tool with full schema coverage and no output schema, the description covers what the tool does, what it matches on, and what comes back. It omits any note about the required context/llm_model analytics params and the conversation_id continuation rule, but those are fully specified in the schema, so the gap is minor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 query, act, play, style, gender, limit and the analytics params. The description's mention that free text matches character, play, or first line merely restates the `query` schema text, and "optional filters" adds no detail beyond what the properties already specify. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Search Shakespeare monologues") plus the matching scope (character, play, first line) and the presence of optional filters. An agent can distinguish it from get_monologue or list_all_monologues_for_a_character, though the description never names a sibling to sharpen the boundary.

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

Usage Guidelines3/5

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

Usage is only implied: search when you want to find monologues by free text. There is no explicit when-to-use/when-not guidance and no mention of the sibling alternatives (get_monologue for a known ID, list_all_monologues_for_a_character for enumeration, random_monologue for discovery), so routing relies on inference.

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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search_monologues

Input Schema

Schema Changelog

TDQS

Glama MCP Gateway

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