identifier_validate
Validate identifier for python/javascript/typescript (keywords + syntax).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| language | No | python |
Validate identifier for python/javascript/typescript (keywords + syntax).
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| language | No | python |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. It only mentions validation for keywords and syntax but does not disclose return format, error behavior, or non-destructive nature. Lacks essential behavioral context.
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?
One-sentence description is extremely concise with no wasted words. Earns its place as a compact summary of purpose.
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?
For a 2-parameter validation tool with no output schema, the description fails to explain what the tool returns (e.g., boolean, errors) or what 'valid' means. Incomplete for agent to correctly interpret results.
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 coverage is 0%, so description must add meaning. It implies 'name' is the identifier and 'language' selects rules, but does not detail what 'name' constraints are or how language affects validation. Adds minimal value beyond schema.
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 clearly states the verb 'Validate' and the resource 'identifier' with specific languages (python, javascript, typescript) and scope ('keywords + syntax'). It distinguishes well from sibling tools like email_validate or json_validate.
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 on when to use this tool versus alternatives. No prerequisites, when-not-to-use, or comparisons with other validation tools in the sibling list.
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.
Every tool has a clear, distinct purpose with thorough descriptions. Even closely related tools like base64_decode/encode and hash_md5/sha256 are easily differentiated by name and description.
All tools follow a consistent lowercase_underscore naming convention, typically in a <domain>_<action> or <action>_<domain> pattern. There are no jarring deviations or mixed styles.
193 tools is an extreme count, far beyond what any focused server needs. While each tool has utility, the sheer number creates a kitchen-sink effect that overwhelms agents and hinders discoverability.
Within each subdomain (JSON, cron, JWT, etc.), the coverage is exhaustive, covering validation, conversion, parsing, and more. Minor gaps exist (e.g., YAML-to-TOML conversion missing), but overall it is remarkably complete.