get_methodology
How dappgrade scores dApps: tiers 0/1/2, three-state checks (pass/fail/not_reached), coverage, and the verdict model. Free.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
dappgrade — onchain app health index
TDQS
A3.8/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only adds 'Free,' which is ambiguous and does not disclose behavioral traits (e.g., read-only, rate limits, output format). The description fails to compensate for missing annotations.
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?
16 words, highly concise, front-loaded with purpose, no wasted elements.
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?
Given no output schema and no parameters, the description adequately covers the tool's purpose and key aspects. It could mention output format but is sufficient for a simple informational tool.
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?
No parameters exist (schema coverage 100%), so the description adds no param info but is not required to. Baseline for 0 parameters is 4.
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 explains the scoring methodology, specifying tiers, checks, coverage, and verdict model. It distinguishes from siblings like get_score (which likely returns scores) and get_universe.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for understanding the methodology, but does not explicitly state when to use it over alternatives like get_score or get_universe, nor provides exclusions.
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
A3.9/5.0
Disambiguation5/5
Each tool targets a distinct aspect: methodology explains scoring, get_score retrieves a verdict for a specific address, and get_universe lists covered dApps. No overlap in purpose.
Naming Consistency5/5
All tool names follow the `get_<noun>` pattern consistently, making the API predictable and easy to navigate.
Tool Count5/5
Three tools is appropriately scoped for the server's purpose: one for explanation, one for querying, one for discovery. No redundancy or missing essentials.
Completeness4/5
Core operations are covered: methodology, scoring, and universe listing. Minor gaps like batch scoring or historical data are absent but not critical for the intended use case.