Store one UTF-8 text document without publishing it or fetching any URL.
| Name | Required | Description | Default |
|---|---|---|---|
| document | Yes | ||
| collection_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
Annotations already establish that this is a non-read-only, idempotent, non-destructive write, and the description is consistent with them. It adds a useful behavioral boundary: the tool does not publish and does not fetch a URL, so callers must pass raw text content. It does not describe side effects such as duplicate handling or quota consumption, but the annotations reduce the need.
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 one short sentence with no filler, front-loading the action and then adding two compact exclusions. It earns its length.
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 simple write tool with an output schema and idempotency annotation, the description is adequate but incomplete: it clarifies the content format and no-fetch behavior, yet does not explain the role of collection_id or how to obtain one. An agent could still call it correctly using the schema and sibling list_personal_rag_collections.
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 0%, so the description needed to explain the parameters. It only hints that 'content' should be UTF-8 text and not a URL; it says nothing about collection_id, title, or tags. The schema names and constraints are available, but the description does not compensate for the lack of parameter documentation.
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 uses a specific verb ('Store') and a specific resource ('one UTF-8 text document'), and adds negative scope ('without publishing it or fetching any URL'). It is unambiguous about the core action, though it does not explicitly differentiate by naming a sibling tool or mention the required collection_id.
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 explicit when-to-use guidance or alternative tool is named. The negatives 'without publishing it or fetching any URL' imply boundaries, but the description leaves the selection context to the agent to infer from the tool name and sibling tools.
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.
Each tool targets a distinct resource and action: problem lifecycle, knowledge reading/search/context, candidate submission/review, and experience verification. Even similar tools like get_knowledge, search_knowledge, and retrieve_context are clearly differentiated by their descriptions.
All tool names follow a consistent snake_case verb_noun pattern with no mixed conventions or vague verbs. Names accurately reflect their actions and objects, making the set predictable and easy to navigate.
At 16 tools, the count is slightly above the typical 3-15 range but still reasonable given the multi-faceted domain (problems, knowledge, candidates, experiences). Each tool appears to have a specific purpose, though a few could potentially be consolidated.
Core workflows are covered: create/claim/manage problems, submit/review candidates, publish/retrieve knowledge, and verify experiences. Minor gaps exist such as no explicit close/cancel operation for problems, but agents can work around these with existing tools.