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conversion_parity_bit

Read-onlyIdempotent

Add or check a parity bit to detect odd numbers of flipped bits in binary strings. Supports even, odd, mark, and space parity schemes.

Instructions

Parity Bit Calculator. Compute or verify a single parity bit for a binary string to support error DETECTION (not correction). In add mode it counts the 1 bits, derives the parity bit for the chosen scheme (even, odd, mark, or space), and appends it to form the codeword; in check mode it splits off the trailing bit, recomputes the expected parity from the leading data bits, and reports whether an error was detected. Parity catches only odd numbers of flipped bits and cannot locate or fix them — use conversion_hamming_code for single-bit correction or conversion_gray_code for transition-error-resistant encoding. Runs locally on the bit string you provide: read-only, non-destructive, offline, and rate-limited (60 requests/min anonymous). Returns the parity bit, the full codeword (add mode), the error-detected flag (check mode), step-by-step working, an explanation, and parity-scheme properties.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesBinary string, digits 0 and 1 only. In check mode it must be at least 2 bits long (data bits plus a trailing parity bit).
modeNoadd appends a computed parity bit to the data; check treats the last bit as the received parity and verifies it against the data bits.add
parityTypeNoParity scheme. even/odd make the total 1 count even/odd; mark forces the parity bit to 1; space forces it to 0.even

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successNoWhether the operation succeeded.
resultNoThe parity calculation or verification result.
Behavior5/5

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

Annotations already denote read-only and idempotent. The description adds rate-limit (60 req/min), offline execution, and details how parity computation works, enhancing transparency without contradicting annotations.

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 well-structured, starting with purpose, then modes, limitations, alternatives, and output. Every sentence adds value; no fluff.

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?

Covers purpose, modes, limitations, alternatives, operational context (read-only, offline, rate-limited), and output details. With output schema present, the description is complete and self-contained.

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 coverage is 100%, but the description provides additional context: constraints (e.g., input length for check mode), purpose of modes and parity types, and examples. This adds value beyond the 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 the tool computes or verifies a parity bit, and distinguishes itself from related tools like conversion_hamming_code and conversion_gray_code by noting it is for detection only, not correction.

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

Usage Guidelines5/5

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

The description explicitly tells when to use (for error detection) and when not (for correction), and suggests alternatives. It also explains the two modes (add/check) and the available parity schemes.

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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