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Buggy1111

anonymize-mcp

by Buggy1111
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

check_readability

Analyze readability of Czech texts with metrics, grammatical rule violations, lexical rarity distribution, and sentence types. Identify complex sentences, rare words, and missing verbs to improve clarity.

Instructions

Analyzuje čitelnost českého textu pomocí PONK — 4 feature sety (v0.7.0).

PONK byl navržen pro úřední komunikaci s občany. V0.7.0 wrapper vystavuje
všechny 4 jeho feature sety, ne jen metriky:

1. **Overall metrics** — ARI (years of education needed), Verb Distance,
   Activity, Lexical diversity. (Always returned.)

2. **Grammatical rules** (``include_rules=True``) — list pravidel které se
   v textu aktivovala. Každé pravidlo má český název a popis. Aktuálně PONK
   detekuje: Nedostatek sloves, Přemíra podstatných jmen, Dlouhé věty,
   Sloveso příliš daleko v klauzi, ...

3. **Lexical surprise** (``include_lexical_surprise=True``) — distribuce
   sémantické překvapivosti slov (1=běžné, 16=velmi vzácné/odborné).
   Vrátí summary: kolik slov je common / surprising / very_surprising.

4. **Speech acts** (``include_speech_acts=True``) — typy vět (Situace,
   Kontext, Postup, Proces, Podmínky, Doporučení, Odkazy, Prameny).

Args:
    text: Vstupní text.
    input_format: ``txt`` (default), ``md``, ``docx``.
    include_rules: Default ``True``. List aktivovaných gramatických pravidel.
    include_lexical_surprise: Default ``True``. Distribuce vzácnosti slov.
    include_speech_acts: Default ``True``. Typy vět/řečové akty.
    include_highlighted_html: Default ``False`` (úspora bandwidthu — HTML
        má 100+ KB). Zapni pro vizualizační report/PDF.

Returns:
    ``metrics``, ``counts``, ``version``, ``processing_time_s``,
    + volitelné ``rules`` (list), ``lexical_surprise`` (dict),
    ``speech_acts`` (dict), ``highlighted_html`` (str).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
input_formatNotxt
include_rulesNo
include_lexical_surpriseNo
include_speech_actsNo
include_highlighted_htmlNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A4.2/5.0
Behavior4/5

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

The description discloses behavioral traits: it mentions PONK is designed for official communication, notes the highlight HTML is large (100+ KB) for bandwidth consideration, and explains the optional feature sets. No annotations exist, so the description carries the burden; it is fairly transparent about what is returned and the cost of certain options.

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

Conciseness4/5

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

The description is well-structured with numbered lists and bullet points, front-loading the purpose. It is reasonably concise for the complexity, though slightly verbose with repeated enumeration of feature sets.

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 the complexity (6 parameters, 1 required, and a rich output schema), the description covers the returned fields and optional components. It is complete enough for an agent to understand outputs, though it could mention that the output schema exists but doesn't need to detail it.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates by explaining each parameter's purpose, default values, and the effect of include flags. It also warns about the highlight HTML size. This adds significant meaning beyond the raw schema.

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 clearly states 'Analyzuje čitelnost českého textu pomocí PONK' and lists four specific feature sets (overall metrics, grammatical rules, lexical surprise, speech acts). It distinguishes itself from sibling tools like analyze_morphology, anonymize, etc., by focusing on readability analysis.

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?

The description explains what the tool does but does not provide explicit guidance on when to use it versus siblings or when not to use it. Usage is implied through the purpose, but no when/when-not or alternative recommendations are given.

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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