html_data_extractor
Structured title, metadata, headings, and links extracted from HTML. Costs $0.10 Base USDC.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes |
DeltaBot Utility Suite
TDQS
C2.4/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses cost, which is a useful behavior, but says nothing about input delivery, return structure, error behavior, or side effects. This is too little for an un-annotated tool.
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?
The description is extremely short, no filler, and front-loads the extraction capability before stating cost. However, the brevity leaves out essential behavioral and semantic details, so it is under-specified rather than genuinely concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one undocumented input parameter and no output schema, the description is far from complete. An agent lacks the information to construct a correct call or interpret the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'input' has no schema properties and 0% schema coverage; description never explains what 'input' should be (HTML content vs. URL). It adds zero meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a clear extraction purpose listing concrete outputs (title, metadata, headings, links) and resource (HTML). However, it doesn't differentiate from sibling tools like seo_meta_audit or website_health which may also analyze HTML.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs the many sibling report and audit tools. No prerequisites or input format stated; an agent cannot determine whether this is for a URL, HTML file, or raw string.
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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TDQS
C2.5/5.0
Disambiguation3/5
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.
Naming Consistency4/5
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.
Tool Count3/5
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.
Completeness3/5
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.