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check_paraphrase

Read-only

Detect paraphrased or reworded content between two texts, even across languages, by comparing semantic similarity of sentences.

Instructions

Finds REWORDED copies between two texts — same meaning, different words, including across languages (e.g. English vs Spanish) — that a literal copy check can't see. It embeds each sentence and compares cosine similarity. NOTE: this SENDS BOTH TEXTS to the SignsOfAI server to embed them (endpoint from SIGNSOFAI_API_ENDPOINT). Requires the embedding feature to be enabled on the server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textAYesFirst document.
textBYesSecond document.
thresholdNoCosine similarity threshold 0..1 to count as a paraphrase. Default 0.72.
Behavior5/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses critical behavioral details: it sends both texts to the SignsOfAI server and requires the embedding feature to be enabled. This is significant operational context not captured by annotations, and there is no contradiction.

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 exactly two sentences: the first states the core purpose, the second covers mechanism, data flow, and requirements. No wasted words; every sentence earns its place.

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?

Without an output schema, the description covers the tool's purpose, method, external data transmission, and prerequisite. It does not explicitly state what the tool returns (e.g., matched sentences, similarity score), which would be helpful. Overall, it is fairly complete for a two-input analysis 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 description coverage is 100% for all three parameters. The description's mention of cosine similarity reinforces the threshold parameter's semantics but does not add new meaning beyond the schema's own description. 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 clearly states the tool finds reworded copies between two texts (same meaning, different words), including cross-language, and explicitly distinguishes itself from literal copy checks. This gives a specific verb+resource and differentiates it from sibling tools like check_originality.

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 provides clear context for when to use the tool (when a literal copy check is insufficient) and notes a prerequisite (embedding feature enabled). However, it does not explicitly name alternative tools or state when not to use it, though sibling context hints at this.

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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