code_diff_summary
Factual code-diff summary. Costs $0.15 Base USDC.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes |
Factual code-diff summary. Costs $0.15 Base USDC.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits itself, but it only adds the cost and 'factual' as a quality cue. It does not mention side effects, permissions, rate limits, or failure behavior.
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 short and the cost sentence is useful, but the brevity crosses into under-specification. It provides barely more information than the tool name and lacks input or usage context, so it is not appropriately sized for a tool with this opaque schema.
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?
Given an opaque input schema, no output schema, no annotations, and many siblings, this description is far too minimal. An agent cannot infer expected input, return format, when to use it, or any operational requirements.
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?
The schema defines a single required 'input' as an opaque object with no property descriptions and 0% schema coverage. The description does not explain what the input should contain, such as diff text, repo references, or base/head commits, so an agent cannot construct valid input.
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 that the tool produces a factual summary of a code diff, which identifies the resource and general output. It lacks an explicit verb and does not distinguish itself from sibling tools, but the core purpose is reasonably clear.
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?
No guidance is given about when to use this tool versus alternatives like changelog_generator or repository_change_radar. There are no context clues, exclusions, or conditions that would help an agent select it confidently.
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 distinguishable by their input source (HTTPS probe, JSON snapshots, OpenAPI, ABI, CSV, etc.), but several report-style tools overlap in purpose, such as changelog_generator vs. release_dependency_risk and csv_profile vs. data_quality_profile. Descriptions help, but an agent could easily hesitate between similarly named change/health/report tools.
All names are lowercase snake_case and generally follow a <domain>_<artifact> pattern, which is predictable and readable. The suffixes vary considerably -- report, summary, digest, audit, health, profile, generator, validator, risk, radar -- so it is not a strict verb_noun convention, but the style is consistent enough.
25 tools is at the upper edge of the borderline-heavy range. The suite spans web, data, repository, security, and wallet domains, so each tool has a plausible place, but the sheer number makes navigation heavier than a typical cohesive toolset.
The suite provides broad coverage for reporting, validation, and change detection, but there are notable gaps such as generic raw data fetching, a generic diff utility, and obvious transforms beyond CSV-to-JSON. For a broadly scoped utility suite, coverage is partial but not severely incomplete.