text_diffDiff two texts (lines/words/chars). $0.002 per call.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | Original text (left side of the diff) | |
| b | Yes | Modified text (right side of the diff) | |
| mode | No | Diff granularity; defaults to lines |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds only the pricing note ($0.002 per call) and does not disclose the output format or any side effects. Given the annotations cover the main behavioral traits, a 3 is appropriate—it adds pricing context but nothing about the result structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence plus a cost note. It is front-loaded with the core action and granularity, and every word earns its place. There is no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool lacks an output schema, so the description should explain what the diff result looks like (e.g., unified diff, structured list of changes). It does not, and also omits any guidance on interpreting the output or handling edge cases. For a tool with three parameters and no output schema, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: each parameter (a, b, mode) has a description. The tool description merely echoes the granularity options already in the enum but adds no new semantic detail. With full schema coverage, the baseline is 3, and the description provides no additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Diff') and resource ('two texts'), and also names the granularity options (lines/words/chars), which clearly distinguishes it from the unrelated siblings. It is immediately obvious what this tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus any alternative, and no exclusions or prerequisites. While the purpose is self-evident for a diff operation, the description fails to provide context about what input it expects (e.g., plain text vs. formatted) or when a different tool might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are cleanly separated by domain prefix (data_, security_, validate_, verify_) and describe distinct outputs. A couple of pairs like token_verdict vs verify_token or data_portfolio vs wallet_dossier could be confused until descriptions are read, but the descriptions resolve the ambiguity.
The majority of tools follow a predictable prefix_subject pattern, e.g. data_block, security_tls, validate_iban, verify_payment. A few outliers like html_to_markdown, text_diff, wallet_dossier, and token_verdict use different conventions, but the overall system remains readable.
20 tools is on the heavy side for the typical MCP server and sits in the 16–25 'feels heavy' zone. Most tools have a legitimate purpose, but the five validate_* identifier tools plus two generic utilities could feel like surface area bloat.
The server covers a broad and coherent read/validation domain: chain data, token safety, payments, security checks, and identifier validators. Minor gaps exist, such as lack of detailed historical transaction/activity data and no general network/domain security scan beyond email, TLS, and typosquat.