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obsify

obsify

by Formative-Sum41
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

redact_text

Replace detected PII in text with placeholders using context and precision rules, with optional known-entities masking from a .obsify.entities file.

Instructions

Return text with detected PII replaced by placeholders (e.g. <AU_TFN>, ). Deterministic; checksum-validated identifiers and context/precision rules apply so bare numbers are not over-masked.

entities is an optional PATH to a local .obsify.entities file of KNOWN names to hide; matches (incl. variants) are masked as <KNOWN_ENTITY>. If omitted, a nearby .obsify.entities is auto-used.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "redact_text"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes
entitiesNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well by disclosing determinism, checksum-validated identifiers, over-masking avoidance, and the entities-file auto-use behavior. Minor gaps remain around error handling or what happens when no PII is detected, but transparency is strong overall.

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 compact and front-loaded: the first sentence states the core operation, followed by key behavioral constraints and then the optional parameter explanation. Every sentence earns its place without unnecessary verbiage.

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

Completeness5/5

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

Given the tool's simple 2-parameter shape and the presence of an output schema, the description is highly complete. It covers the main transformation, important edge-case prevention (bare numbers), and the optional entities file behavior. The description is sufficient for an agent to invoke the tool correctly without needing further clarification.

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%, so the description must compensate, and it does. It explains that `entities` is a path to a local `.obsify.entities` file, that matched names are masked as `<KNOWN_ENTITY>`, and that a nearby file is auto-used if omitted. This adds substantial meaning beyond the bare schema fields.

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 first sentence clearly states the verb (redact), the resource (text), and the output format (PII replaced by placeholders), making the purpose immediately obvious. It also distinguishes itself from sibling tools like scan_pii and verify_value_free by explicitly conveying the redaction 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 provides clear context about how the tool behaves and when the optional entities file applies, but it does not explicitly state when to prefer redact_text over sibling tools or when not to use it. There are no alternative tool comparisons or exclusions.

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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