Skip to main content
Glama
kpshinnik

docs-masked

by kpshinnik

docs-masked

Lokale Anonymisierung von Dokumenten vor dem Senden an ein Sprachmodell — und Rückeinsetzung nach der Antwort.

Das Dokument verlässt den Rechner nie in seiner ursprünglichen Form. Personenbezogene Daten werden durch stabile Tags (#PERSON_1#, #PHONE_2#, #ADDRESS_1#) ersetzt, an das Modell wird nur der Text mit Tags gesendet, und die erhaltene Antwort wird lokal anhand des Sicherungsspeichers wieerhergestellt.

документ ──▶ маска ──▶ контроль утечки ──▶ модель ──▶ обратная подстановка
           локально      локально          сеть           локально

Funktioniert als Skil für Claude Code, als MCP-Server für jeden anderen Agenten und als normales Kommandozeilen-Werkzeug.

Wie es funktioniert

1. Maske. Das Dokument wird in Textfragmente zerlegt – Absätze, Zelen, Markup-Knoten. In jedem werden personenbezogene Daten gefunden, jeder Wert erhält einen stabilen Tag. Dieselbe Person erhält denselben Tag im gesamten Dokument, einschließlich Kasusvarianten und Initialen: „Иванов Иван Иванович“, „Иванову“ und „Иванов И.И.“ – das ist ein #PERSON_1#.

2. Leckontrolle. Der maskierte Text wird erneut durch alle Detektoren plus einen paranoiden Durchlauf gejagt: jedes @, jede Kette von sieben oder mer Ziffern, jede telefonähnliche Sequenz. Wenn etwas übrig blebt, wird der Versand blockiert – durch eine Exception, nicht durch eine Warnung im Log.

3. Senden. Nach außen geht nur der Text mit Tags. Der einzige Netzwerkausgang ist die Funktion lm.send(), und sie muss vor der Anfrage eine Prüfung aufrufen. Jeder Versand wird im Logbuch ~/.pii_shield/egress.jsonl protokoliert: Zeit, Anbeter, Model, Größe, sha256, Prüfstatus. Der Inhalt wird nicht geschrieben.

4. Rückeinsetzung. Die Antwort des Modells durchläuft den Sicherungsspeicher: Tags werden durch Originale ersetzt. Für vollständige Namen wird der wiederhergestellte Nominativ eingesetzt – wenn die Person im Dokument nur als „Кузнецову Ивану Петровичу“ erwehnt wird, wird sie in der Antwort zu „Кузнецов Иван Петрович“.

Related MCP server: Doc Sanitizer MCP Server

Installation

git clone https://github.com/kpshinnik/docs_masked.git ~/.docs_masked/src
cd ~/.docs_masked/src && ./install.sh

Das Skript installiert Abhängigkeiten, lekt den Skil in ~/.claude/skils/docs-masked ab und druckt das fertige MCP-Konfigurationsfragment aus. Details und Varianten – in docs/INSTALL.md.

Verbindung zum Agenten

Methode

Für wen

Wie

Skil

Claude Code, Claude.ai

./install.sh oder /plugin marketplace add kpshinnik/docs_masked

MCP-Server

Cursor, Windsurf, Codex CLI, Continue, Zed, Cline, Claude Desktop

python3 mcp_server.py als stdio-Server

CLI und Regel

alles andere

Befehle im Terminal plus templates/AGENTS-rule.md in das eigene Projekt

Schritt für Schritt für jedes Harness – docs/HARNESSES.md.

Der MCP-Server ist ohne Abhängigkeiten geschrieben: nur python3 wird benötigt. Er bietet sechs Werkzeuge – mask_text, unmask_text, verify_text, scan_document, mask_document, unmask_document.

Verwendung

docs-masked scan   договор.docx                    # что будет скрыто
docs-masked mask   договор.docx                    # маска + сейф
docs-masked report договор.docx --open             # посмотреть глазами
docs-masked ask    договор.docx -p "Найди риски по срокам"
docs-masked unmask договор.masked.docx --vault договор.docx.vault.json

Befehle

Befehl

Was es tut

scan FILE

Zeigt, was maskiert wird. Datei wird nicht geändert, Netzwerk nicht benutzt.

mask FILE

Anonymisierte Kopie im selben Format plus Sicherungsdatei.

unmask FILE --vault V

Stelt die Originale wieder her.

verify FILE

Überprüft, dass keine personenbezogenen Daten mehr vorhanden sind.

ask FILE -p "..."

Volständiger Kreislauef: Maske → Prüfung → Model → wiederhergestellte Antwort.

report FILE

HTML-Übersichtsseite: jeden Ersatz im Kontext, Werte ausgebendet.

selftest

Selbstest des Kreislauefs.



Vollständige Liste der Flags – skils/docs-masked/references/cli.md.

Was erkannt wird

Vollständige Namen in jedem Kasus (Russisch, Lateinschrift, Transliteration), Organisationen, Adressen, E-Mail, Telefone, Pass und Code der Ausgabestelle, SNILS, INN, OGRN, KPP, BIK, Abrechnungskonten, Bankkarten, IBAN, OMS-Versicherungspolice, Führerscheine, Kennzeichen, IP-Adressen, @Benutzernamen, Geburtsdaten und Ausstellungsdaten von Dokumenten, Requisiten-Codes (OKTMO, OKPO, KBK), plus Ihre eigenen Zeilen.

Die Identifikatoren werden echt geprüft: Prüfsumme von SNILS, Prüfziffern von INN und OGRN, Luhn-Algorithm für Karten, mod-97 für IBAN. Vollständige Tabelle – references/coverage.md.

Formate

Format

Lesen

Schreiben an Ort und Stelle

.txt .md .rst .log .tex .yaml .ini

ja

ja

.docx

ja

ja, unter Erhaltung der Formattierung

.xlsx .xlsm

ja

ja

.csv .tsv

ja

ja

.json

ja

ja

.html .htmm

ja

ja

.pdf

ja

mit Flag --pdf-redact, mit physischer Schwärzung

.rtf .doc .odt

ja

nein (nur macOS, über textutil)

DOCX wird über XML durchlafen, nicht über document.paragraphs: sonst gehen Absätze in Inhaltsfeldern und Überschriften verloren – in einem richtigen Vertrag ging dadurch eine ganze Salte des Requisitenblocks verloren. In Tabellen wird der Saltenkopf als Kontext genutzt: eine Zelle 500100732259 ist an sich nicht von einer zufälligen Zahl unterscheidbar, aber in der Salte „INN“ wird sie sicher erkannt.

Python-API

from pii_shield import ask_document

res = ask_document("договор.docx", "Составь резюме и найди риски",
                   provider="anthropic")
print(res.answer)          # имена уже восстановлены

Manuelle Kontrol jedes Schrits:

from pii_shield import mask_text, assert_clean, unmask_text

r = mask_text(raw)                 # r.text — с тегами, r.vault — сейф
assert_clean(r.text)               # LeakGuardError, если что-то осталось
answer = call_model(r.text)        # наружу уходит только маска
final, unknown = unmask_text(answer, r.vault, mode="canonical")

Weiteres – references/api.md.

Sicherungsspeicher (Vault)

Der Sicherungsspeicher ist das Einzige, was Tags mit Originalen verbindet. Ohne ihn ist die Rückeinsetzung unmöglich.

  • Wird neben dem Dokument als <datei>.vault.json geschrieben, Berechtigung 0600.

  • Wird mit dem Flag --pass-env verschlüselt (scrypt + Fernet).* Speichert die kanonische Form, alle gefundene Varianten und ein Ereignisprotokol der Vorkommen in der Reihenfolge des Dokuments – dank des Protokolls stellt die genaue Wiederherstelling die ursprüngliche Wortform wieder her, nicht die kanonische.

  • Ist in .gitignore aufgenommen. Commiten Sie ihn nicht.

Genauigkeit und Grenzen

Das Werkzeug ist so ausgelegt, dass es im Zweifel auf die sichere Seite irrt: lieber zu viel maskieren als etwas übersehen. Was Sie wissen solten:

  • Scan-PDF ohne Textebene wird nicht verarbeitet – OCR wird benötigt.

  • Namensvetter ohne Initialen erhalten getrennte Tags, verschmelzen nicht zu einer Person.

  • Eine nackte Zahl ohne Hinweise kann als Identifikator nicht erkannt werden – aber der paranoide Durchlaf wird solhen Text dennoch nicht nach außen lasen.

  • Beliebige lateinische Namen ohhe slawische Endungen und ohhe Anrede (Mr., Dr.) werden nicht erkannt: jedes Par von Großbuchtaben zu erfasen würde mehr Schaden als Nutzen bringen.

Bei einem kritishen Dokument lohnt es sich, docs-masked report einmal mit den Augen anzuschauen.

Entwicklung

python3 -m pytest tests/ -q          # тесты
python3 -m pii_shield.cli selftest
python3 samples/make_samples.py      # пересоздать тестовые документы

Invarianten, die nicht verletzt werden dörfen, sind in AGENTS.md aufgeführt. Ales in samples/ ist synthetisch; das Verzeichnis examples/ ist für Ihre lokalen Dokumente reserviert und gelangt nicht in das Repository.

Lizenz

MIT.

Available Tools

6 tools
mask_documentB

Создать обезличенную копию файла в том же формате и сейф соответствий рядом. Для DOCX/XLSX сохраняется форматирование, для PDF доступно физическое вымарывание (pdf_redact).

NameRequiredDescriptionDefault
outNoкуда положить копию
pathYes
allowlistNoстроки, которые маскировать не нужно
mask_urlsNoскрывать ссылки
tag_styleNoформат тега: #PERSON_1# | [[PERSON_1]] | <PERSON_1>
pdf_redactNo
vault_pathNo
extra_termsNoдополнительные строки для маскирования
include_textNoвернуть замаскированный текст в ответе
mask_all_datesNoскрывать все даты, не только даты рождения
aggressive_namesNoскрывать одиночные слова, похожие на фамилии

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It explains that the tool creates a copy (non-destructive), preserves formatting for certain types, and has a PDF redaction option. However, it does not describe what the 'safe of matches' is, whether it modifies the original, or any other behavioral aspects like idempotency or authorization requirements. Some transparency but incomplete.

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 short at two sentences, with the main action in the first sentence. It avoids clutter but omits important details like the purpose of the 'safe of matches'. It is reasonably concise, though the second sentence could be more integrated.

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

Completeness2/5

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

Given the tool has 11 parameters covering many masking options and no output schema, the description is insufficient. It explains basic file copying and format handling but fails to describe the extensive configuration options (allowlist, URL/date masking, name detection) or the structure of the 'safe of matches' output. The agent would need to rely heavily on parameter descriptions, which are incomplete (only 73% coverage).

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 73%, so the baseline is 3. The description adds no extra parameter details beyond what the schema already provides. It mentions PDF redaction (pdf_redact) but doesn't elaborate on other parameters like allowlist, out, or vault_path. Thus the description does not enhance parameter semantics.

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?

The description clearly states the primary action: creating an anonymized copy of a file and a safety mapping. It specifies different behaviors for DOCX/XLSX vs PDF, adding context about format support. However, it does not explicitly distinguish from sibling tools like mask_text or unmask_document, though the document focus is implied.

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?

The description provides no guidance on when to use this tool versus its siblings such as mask_text for text strings or scan_document for scanning. It lacks any conditions, prerequisites, or recommended use cases, leaving the agent to infer applicability solely from the tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

mask_textA

Заменить персональные данные в тексте на устойчивые теги (#PERSON_1#, #PHONE_2#). Вызывай это ДО того, как отправишь чужой текст куда-либо. Возвращает vault_id для обратной подстановки.

NameRequiredDescriptionDefault
textYes
allowlistNoстроки, которые маскировать не нужно
mask_urlsNoскрывать ссылки
tag_styleNoформат тега: #PERSON_1# | [[PERSON_1]] | <PERSON_1>
extra_termsNoдополнительные строки для маскирования
mask_all_datesNoскрывать все даты, не только даты рождения
aggressive_namesNoскрывать одиночные слова, похожие на фамилии

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that it returns a vault_id for reverse substitution, but does not explain whether the operation is destructive, reversible beyond substitution, or has any side effects like logging or API rate limits.

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 extremely concise with two sentences: the first explains what the tool does, the second gives critical timing advice. Every sentence adds value with no redundancy.

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 parameter richness (7 params, 86% schema coverage) and lack of output schema, the description adequately covers the main purpose and usage timing. It could improve by mentioning return value structure or error states, but it is sufficient for an agent to correctly select and invoke the 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 coverage is 86%, so the baseline is 3. The description does not add extra meaning beyond the schema's descriptions (e.g., the allowlist, tag_style formats are already documented). The only added value is the overall workflow context, not parameter-specific details.

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 the verb 'replace' and resource 'personal data in text', specifies the output format of stable tags like #PERSON_1#, and distinguishes itself from siblings like unmask_text and mask_document by focusing on text-level masking.

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?

The description explicitly says 'Call this BEFORE sending someone else's text anywhere', providing clear timing guidance. However, it does not explicitly state when not to use it or describe alternative tools like verify_text or mask_document for comparison.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

scan_documentA

Показать, что будет скрыто в файле: количество и типы находок. Файл не изменяется, оригиналы значений не возвращаются. Форматы: .csv, .doc, .docx, .htm, .html, .ini, .json, .log, .markdown, .md, .odt, .pdf, .rst, .rtf, .srt, .tex, .tsv, .txt, .wordml, .xhtml, .xlsm, .xlsx, .yaml, .yml

NameRequiredDescriptionDefault
pathYes
allowlistNoстроки, которые маскировать не нужно
mask_urlsNoскрывать ссылки
tag_styleNoформат тега: #PERSON_1# | [[PERSON_1]] | <PERSON_1>
extra_termsNoдополнительные строки для маскирования
mask_all_datesNoскрывать все даты, не только даты рождения
aggressive_namesNoскрывать одиночные слова, похожие на фамилии

TDQS

A4.2/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It explicitly states the file is not modified and original values are not returned, which are key behavioral traits for a scan tool. It also lists supported formats, providing additional transparency.

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, front-loaded with the main purpose and key guarantees, followed by a compact list of supported formats. No extraneous words.

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?

The description explains the tool's output nature (counts and types, no original values) but lacks a detailed return structure or error handling expectations. Given no output schema, it could be more explicit, but for a scan tool with 7 params, the provided information is reasonably complete.

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 coverage is 86% (6/7 parameters have descriptions), so the schema already explains parameter meanings. The description itself does not add parameter details beyond noting file formats, which corresponds to the 'path' parameter but is already partially covered by the schema. Baseline 3 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 ('Показать' - show) and resource ('что будет скрыто в файле'), clearly indicating a preview/scan function that counts and types findings. It distinguishes from siblings like mask_document (which actually modifies the file).

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 implies usage for non-destructive previewing but does not explicitly contrast with mask_document or other sibling tools. It provides clear context (file not modified, original values not returned) but no explicit when-to-use vs alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

unmask_documentC

Восстановить оригиналы в ранее замаскированном файле по сейфу.

NameRequiredDescriptionDefault
outNo
modeNo
pathYes
vault_pathYes

TDQS

C2/5.0
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 only states the action ('restore originals') without revealing side effects, whether the operation is destructive, authentication requirements, or any rate limits. The description is insufficient for an agent to understand the tool's behavior.

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

Conciseness2/5

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

The description is a single sentence, but it is not concise because it is under-specified and in a non-English language, failing to efficiently convey necessary information. It does not earn its place as a useful guide.

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

Completeness1/5

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

With 4 parameters (2 required), no output schema, and no annotations, the description is critically incomplete. It does not explain return values, prerequisites, parameter behavior, or any operational context. The agent cannot determine how to invoke the tool correctly.

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

Parameters1/5

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

Schema description coverage is 0%, and the description adds no meaning to any parameter. The parameter names (out, mode, path, vault_path) are not explained, and the enum mode (sequential/canonical) is left undefined. The description does not compensate for the lack of schema descriptions.

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 states the tool restores originals in a previously masked file by vault, which is a specific verb+resource. However, it is in Russian, which may reduce clarity for non-Russian-speaking agents. It distinguishes from siblings like mask_document and unmask_text, but the phrase 'by vault' is ambiguous and does not fully align with the parameter name 'vault_path'.

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?

No guidance is provided on when to use this tool vs alternatives such as mask_document or unmask_text. There is no mention of prerequisites (e.g., the file must have been previously masked) or context for when unmasking is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

unmask_textB

Вернуть оригиналы вместо тегов по сейфу. mode=canonical — для ответа модели (ФИО в именительном падеже), mode=sequential — точное восстановление ранее замаскированного текста.

NameRequiredDescriptionDefault
modeNo
textYes
vault_idYesидентификатор из mask_text или путь к файлу сейфа

TDQS

B3.3/5.0
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 that the tool returns originals from a vault and describes two modes, but it does not disclose whether the operation is read-only, whether it modifies the vault, what happens on invalid vault_id or text, or any side effects. For a tool that likely interacts with a vault, this is a significant gap.

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 concise: two sentences conveying purpose and mode details. The first sentence clearly states the action, and the second elaborates on modes. It is front-loaded and efficient, though it could be slightly more structured (e.g., separating mode descriptions) without losing brevity.

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

Completeness2/5

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

Given the tool has 3 parameters, no output schema, and no annotations, the description is incomplete. It explains modes but does not describe the return format, prerequisites (e.g., that text must have been previously masked), error conditions, or the behavior of the text parameter. The lack of output schema information means the agent has no idea what the tool returns. This is insufficient for safe and correct invocation.

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 only 33% (only vault_id has a description). The description adds meaning for the mode parameter by explaining the two enum values, but it does not describe the text parameter at all. The vault_id parameter's schema description already covers its purpose. Overall, the description partially compensates for the low schema coverage by clarifying the mode parameter, but the text parameter remains undocumented.

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 the tool's purpose: 'Return originals instead of tags from the vault.' The two modes (canonical for model response, sequential for exact restoration) further specify what the tool does. The name and sibling tools (mask_text, unmask_document) help distinguish it as a text-level unmasking operation.

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 when to use each mode (canonical for model response, sequential for exact restoration), but it does not explicitly state when to avoid this tool, nor does it compare it to alternatives like unmask_document or verify_text. The guidance is implicit through the mode descriptions, but lacks explicit exclusions or context for choosing between siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

verify_textC

Проверить, что в тексте не осталось персональных данных. safe_to_send=false означает, что отправлять нельзя.

NameRequiredDescriptionDefault
textYes
allowlistNoстроки, которые маскировать не нужно
mask_urlsNoскрывать ссылки
tag_styleNoформат тега: #PERSON_1# | [[PERSON_1]] | <PERSON_1>
extra_termsNoдополнительные строки для маскирования
mask_all_datesNoскрывать все даты, не только даты рождения
aggressive_namesNoскрывать одиночные слова, похожие на фамилии

TDQS

C2.9/5.0
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 reveals that the tool returns a result where 'safe_to_send=false' means the text cannot be sent, but it omits many critical details: whether the tool has side effects, what the exact output structure is, authentication requirements, or rate limits. The description is too minimal for a tool with 7 parameters.

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, concise and front-loaded: first sentence states purpose, second explains a key output indicator. No redundant information. For a tool with a single core action, this is appropriately sized.

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

Completeness2/5

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

Given 7 parameters and no output schema, the description is notably incomplete. It does not explain the return value format (e.g., boolean, object with 'safe_to_send'), how parameters like 'mask_urls' or 'tag_style' influence verification, or how this tool relates to the sibling 'scan_document' (both seem to check PII). An agent would lack essential context to use it correctly.

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 86% (6 of 7 parameters have descriptions), so baseline is 3. The tool description does not add any commentary on parameters beyond what the schema already provides. For example, it doesn't explain how 'allowlist' or 'aggressive_names' affect the verification logic. The description thus provides no additional value for parameter understanding.

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?

The description states the verb 'Проверить' (check) and resource 'текст' (text), clearly indicating it verifies absence of personal data. It also hints at the output semantics with 'safe_to_send=false'. This differentiates it from siblings like mask_text (which modifies) and scan_document (which likely processes documents). However, it does not explicitly specify the return type (e.g., boolean or object), slightly reducing clarity.

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?

The description provides no guidance on when to use this tool versus alternatives like mask_text or scan_document. There is no mention of prerequisites, typical workflows (e.g., 'call after masking'), or exclusions. The sibling tools suggest different operations, but the description does not help an agent decide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 6 tool updatesv1.0.0
    • First observedmask_document
    • First observedmask_text
    • First observedscan_document
    • First observedunmask_document
    • First observedunmask_text
    • First observedverify_text

TDQS

A3.5/5.0

Scored across 6 tools

Disambiguation5/5

Each tool targets a distinct operation (mask vs unmask, text vs file) and the descriptions clearly differentiate text vs document variants. No two tools could be confused for the same purpose.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case: mask_text, unmask_text, verify_text, scan_document, mask_document, unmask_document. The verbs are predictable and the nouns clearly indicate the resource type.

Tool Count5/5

With exactly 6 tools, the server is well-scoped for the domain of personal data masking/unmasking. Each tool serves a necessary role without redundancy, covering both text and document workflows in a focused manner.

Completeness5/5

The tool surface covers the full lifecycle: mask (text+document), unmask (text+document), verification, and preview. There are no obvious gaps—the server provides everything needed to protect and restore personal data in both free text and structured documents.

Maintenance

ActivityStale
ResponsivenessNo issues

Related MCP Connectors

Related MCP Servers

  • F
    license
    Not graded
    quality
    D
    maintenance
    MCP server for automatic detection and redaction of PII in text, with anonymization and deanonymization capabilities, all local processing.
    1
    -
  • A
    license
    A
    quality
    B
    maintenance
    An MCP server that redacts PII/PHI from text before it ever reaches an LLM — self-hosted, fail-closed, and HIPAA-aware.
    3
    25 PyPI
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    MCP server providing on-prem PII detection and anonymization tools (scan and is_sensitive) for AI agents, ensuring data stays local.
    4
    MIT