x402-code-diagnose: Code diagnosis: syntax check + 9 bug patterns
| Name | Required | Description | Default |
|---|---|---|---|
| code | No | Code to process | |
| lang | No | Lang to process | |
| source | No | Source to process | |
| language | No | Language to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions syntax check and 9 bug patterns, but does not disclose whether the tool is read-only, whether it requires network access, how it handles invalid code, whether it returns diagnostics with severity levels, or what happens with unsupported languages. For a code-analysis tool with no annotations, this is a notable gap.
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 front-loaded, but it is telegraphic and reads more like a tagline than a functional explanation. The phrase '9 bug patterns' is vague without enumerating or linking those patterns. It is concise but borderline under-specified.
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 has no output schema, no annotations, and four parameters with redundant-sounding names. An agent would need to know which parameter to use, what languages are supported, what the 9 bug patterns are, and what the output format looks like. Given that sibling tools like x402-ai-code-review and x402-ai-code-explain exist, the description is incomplete for confident selection and correct invocation.
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%, with all four parameters described as 'Code to process', 'Lang to process', 'Source to process', and 'Language to process'. The description does not add meaning beyond the schema, and it leaves ambiguity between 'code' vs 'source' and 'lang' vs 'language'. With 100% schema coverage, a baseline of 3 is appropriate, but the description misses the opportunity to clarify parameter aliases or preferences.
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 'Code diagnosis: syntax check + 9 bug patterns' clearly states a specific verb (diagnose) and resource (code), and conveys the core functionality: syntax checking plus nine bug pattern detections. It does not explicitly distinguish itself from sibling tools like x402-ai-code-review, x402-ai-code-explain, or x402-code-pipeline, but its named output scope (syntax + bug patterns) gives reasonable specificity.
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?
The description provides no guidance on when to use this tool versus siblings such as x402-ai-code-review, x402-code-pipeline, or x402-dockerfile-lint. It does not state what inputs are expected (e.g., which languages are supported, whether code snippets or full files are expected), nor does it explain what '9 bug patterns' means in practice.
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.
The tool set is saturated with near-duplicates and synonyms: character-count vs char-count, clamp vs clamp-value, is-abundant vs is-abundant-num vs is-abundant-number, and fetch vs browser-scrape vs web-scrape vs text-scrape. Generic names like 'difference', 'normalize', 'range', and 'partition' make the boundaries even harder for an agent to determine.
Most tools share a x402- kebab-case prefix, but the set mixes noun-only names (math, hash, prime, time), verb-first names (get_stats, find, validate), auto-generated names (x402-publish-1787853294312-base-account), and inconsistent variants like temp vs temperature vs temperature-convert. This is not a coherent verb_noun convention despite the common prefix.
1677 tools is an extreme count that creates selection paralysis and makes coherent agent use impractical. A utility or marketplace server at this scale needs sub-services or namespacing rather than a flat tool list.
The surface has broad token coverage across many utility categories, but the marketplace aspect is incomplete: service_discovery and get_stats exist, yet there are no generic publish, update, delete, or account-management operations. Utility families also contain redundant variants without clear completion or lifecycle structure.