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Shakespeare's Monologues

by io.github.slshults
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get_paraphrased_monologue

Fetch 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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoThe monologue's numeric id (from search_monologues).
contextYesExplain 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_idNoDeprecated alias for `id`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedInput schema / properties / id / description
      Previous value: -"The monologue's numeric id."New value: +"The monologue's numeric id (from search_monologues)."
    • addedInput schema / properties / monologue_id
      Added value: +{
+  "description": "Deprecated alias for `id`.",
+  "type": "integer"
+}
    • changedInput schema / required
      Previous value: -[
-  "id",
-  "context"
-]New value: +[
+  "context"
+]
  2. Changed3 schema fields changed
    • 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"
+}
    • changedInput schema / required
      Previous value: -[
-  "id"
-]New value: +[
+  "id",
+  "context"
+]
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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.

Conciseness5/5

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.

Completeness4/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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.

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