package_scripts_list
List scripts from package.json or pyproject.toml (poetry/PEP 621). When: List npm/poetry/PEP 621 scripts from manifests.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | auto | |
| text | Yes |
List scripts from package.json or pyproject.toml (poetry/PEP 621). When: List npm/poetry/PEP 621 scripts from manifests.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | auto | |
| text | Yes |
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 are provided, so the description carries full burden. It does not disclose output format, file system interaction, or mutation behavior. The tool is likely read-only, but this is not confirmed.
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 two sentences, but the second sentence repeats the first. It could be more concise and front-loaded. No structural issues beyond redundancy.
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 no output schema, the description should explain what the tool returns. It does not. Also, it does not specify whether 'text' is file content or a path, leaving ambiguity for a tool with only two parameters.
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%, meaning the description does not explain parameters. The 'text' parameter's role (content vs. path) is ambiguous, and 'kind' is not explained despite being an enum.
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 it lists scripts from package.json or pyproject.toml. It specifies the verb (list) and resource (scripts from manifests), but the second sentence is redundant, slightly lowering clarity.
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 'When' prefix explicitly tells when to use this tool. There are no similar sibling tools, so alternatives aren't needed, but it lacks explicit exclusions or prerequisites.
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.