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Tanod MCP server

utilpeek: diff two texts (line, word or character)

diff_text
Read-onlyIdempotent

Compare two texts to get unified line diffs, word or character changes, similarity ratio, and exact change offsets for review or validation.

Instructions

utilpeek: Diff two texts: unified line diff, word or character changes. For PDF or Word files use compare_documents. Returns the differences between two texts: similarity ratio, counts and hunks; in line mode a git-compatible unified diff, in word or char mode change records (equal, insert, delete, replace) with exact character offsets into a and b. At most 1,000 hunks and 5,000 change records, then truncated. Parsed in an isolated, resource-limited child process without network; input over its limits is a 422 (not charged). Typically under 0.5 s. Price: USD 0.001. Free: 10 utilpeek calls per IP per UTC day. The submitted text is never logged or stored. Docs: https://tanod.dev/learn/text-diff-api.html

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aYesThe old text (at most 100,000 characters).
bYesThe new text (at most 100,000 characters).
modeNoline (default; a unified diff), word or char (at most 20,000 characters per side).line
contextNoUnchanged lines around each hunk (0-10, default 3).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo
errorNoOnly on an error result: an object {code, message}, or the reason string of an x402 PaymentRequired object.
hunksNo
statsNo
sourceNo
changesNo
contextNo
unifiedNo
identicalNo
truncatedNo
similarityNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing output truncation limits (1,000 hunks / 5,000 change records, then `truncated`), sandboxing ('isolated, resource-limited child process without network'), the failure mode (over-limit input → 422, not charged), latency (~0.5 s), pricing, free-tier quota, and the data-retention guarantee ('never logged or stored'). For a stateless read tool this is unusually complete operational context.

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?

Front-loads the purpose and the sibling routing rule before operational details, and the density is high with little waste. It is on the long side for a 4-parameter utility — the pricing, quota and docs-link clauses are useful but push it toward a wall of text.

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 an output schema exists, the description needn't explain return values, yet it still summarizes the shapes and truncation behavior. Combined with limits, error semantics, isolation and latency, an agent has everything needed to call this correctly and interpret failure.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3 and the schema already documents a, b, mode and context. The description adds value the schema cannot: what each mode actually returns (git-compatible unified diff vs. equal/insert/delete/replace records with exact offsets into a and b), which is the key semantic distinction between the enum values.

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?

States a specific verb+resource ('Diff two texts') and enumerates the three granularities it supports. It actively distinguishes itself from the closest sibling by name: 'For PDF or Word files use compare_documents.' An agent can route correctly without opening either schema.

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?

Provides an explicit when-not rule with the alternative named ('For PDF or Word files use compare_documents'), which is the primary ambiguity against this sibling set. The mode descriptions (line = unified diff, word/char = change records with offsets) also imply when each granularity is appropriate.

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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