cookie_header_parse
Parse Cookie request header into name/value map. When: Parse Cookie request headers.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| header | Yes |
Parse Cookie request header into name/value map. When: Parse Cookie request headers.
| Name | Required | Description | Default |
|---|---|---|---|
| header | 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?
With no annotations, the description must fully disclose behavioral traits. It mentions the output is a 'name/value map' but does not detail how malformed headers are handled, whether the 'Cookie:' prefix is expected, or any limitations. No destructive or read-only hint is implied, leaving ambiguity.
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 is redundant ('When: Parse Cookie request headers'). It is short but could be more concise by merging the two sentences. The structure is adequate but not efficient.
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 that there is no output schema, the description should clarify the return format beyond 'name/value map'. It does not address error handling, edge cases, or behavior with multiple cookies. For a simple parsing tool, it is minimally complete but lacks details needed for reliable 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?
The input schema has one parameter 'header' with no description and 0% schema coverage. The description does not elaborate on the expected format (e.g., should it include the 'Cookie:' label or just the value?), leaving the agent to guess. No enums or examples are provided.
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 parses a Cookie request header into a name/value map, which is a specific verb and resource. It distinguishes itself from sibling tools like http_headers_parse that parse all headers, but could be more explicit about its unique purpose.
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: Parse Cookie request headers' line essentially repeats the purpose without providing guidance on when to use this tool versus alternatives, such as using a general HTTP header parser or cookies from a parsed request object. No exclusions or context are given.
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.