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zoombulous

humor-mcp

by zoombulous

style_pack

Generate a compact, paste-ready style brief with exemplars, liked/disliked calibration, and required attribution blocks for any humor output, optionally focused on a specific topic.

Instructions

A compact, paste-ready style brief: exemplars, liked/disliked calibration, and the attribution block that must travel with any output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNohow many examples per side (capped at 200)
topicNofocus the exemplars on a subject; omitted = highest-rated overall
include_hiddenNoinclude packs the corpus owner marked off-rubric — their licence is fine, they were judged unrepresentative
include_restrictedNoinclude packs whose LICENCE bars redistribution (local reference only)
Behavior2/5

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. It mentions the tool includes packs that may be 'off-rubric' or 'restricted' based on parameter docs, but the description itself doesn't disclose what gets generated, whether any mutation occurs, license/reuse implications, or output format. The 'attribution block that must travel' hints at a licensing expectation but doesn't explain its mechanics or consequences.

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

Conciseness3/5

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

The description is a single sentence and compact, which is good. However, it packs in several undefined jargon terms ('exemplars', 'liked/disliked calibration', 'attribution block') that force the reader to parse marketing-style language for meaning. It's concise but not maximally clear; front-loading a plain-verb statement of the operation would serve the agent better.

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

Completeness3/5

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

For a read-style tool with full schema coverage and no output schema, the description is adequate but leaves gaps. It doesn't clarify the return format (is it text, structured data?), how restricted packs are handled in output, or why/when to enable the hidden and restricted flags. Given four boolean/integer parameters influencing output content and licensing-sensitive behavior, the description could meaningfully expand on when those flags matter, which it does not.

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 each parameter (n, topic, include_hidden, include_restricted) is documented in the schema itself. The description adds no parameter-specific meaning beyond what the schema provides; it references 'exemplars' and 'calibration' generically but doesn't clarify how 'n' maps to sides, or what 'liked/disliked calibration' means operationally. Per baseline for full schema coverage, a 3 applies.

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

Purpose3/5

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

The description reads like a marketing blurb ('compact, paste-ready style brief') using jargon ('exemplars', 'liked/disliked calibration', 'attribution block') that isn't precisely defined. It conveys a general sense that this produces a style summary with examples, but doesn't clearly state the tool's verb-resource operation (e.g., 'Generate a style brief'). The jargon and stylistic phrasing obscure rather than clarify the core purpose, distinguishing it only weakly from siblings like taste_profile and preference_pairs.

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

Usage Guidelines2/5

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

There is minimal guidance on when to use this tool. The description references an 'attribution block that must travel with any output,' implying a downstream requirement, but doesn't explicitly state when to prefer this over search_humor, taste_profile, preference_pairs, or breakdown. No exclusions or alternatives are mentioned, and the context of 'style' vs. sibling concepts like 'taste' or 'humor' is left implicit.

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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