Send kapoost a longer message. context REQUIRED (why you're writing / which piece / which task). contact optional — without it no reply is possible.
| Name | Required | Description | Default |
|---|---|---|---|
| from | No | ||
| text | Yes | ||
| contact | No | ||
| context | Yes | ||
| regarding | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses the critical constraints (context required, contact optional for replies), but does not mention other behavioral aspects such as return values, length limits, or any side effects beyond sending.
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, front-loaded with the action and key requirements. Every word adds value, with no extraneous information.
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 tool with 5 parameters and no output schema, the description explains only two parameters and lacks return-value details. It is adequate for a simple messaging tool, but the gaps in parameter semantics and behavioral disclosure prevent a higher score.
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 must compensate. It explains the meaning of 'context' and 'contact', but omits 'text', 'from', and 'regarding'. Additionally, it only highlights context as required, while the schema also requires text, which may mislead the agent.
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 action ('Send kapoost a longer message') and identifies the resource (kapoost). The word 'longer' differentiates it from sibling tools like leave_comment, implying a distinct use case.
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 clear guidance on prerequisites: context is required, contact is optional but necessary for a reply. It implies a longer message use case compared to leave_comment, but does not explicitly name alternatives or exclusion cases.
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.
Most tools have clearly distinct purposes with detailed descriptions, but a few boundaries are fuzzy: leave_message vs ask_human vs leave_comment, and list_content vs list_collection could confuse an agent at first glance. Overall, the descriptions are thorough enough to disambiguate.
The naming convention is predominantly snake_case with verb_noun structure (list_content, read_blob, upsert_skill). Minor deviations exist such as the mysloodsiewnia_* prefix and British spelling in synthesise_persona_patterns, but the pattern is highly recognizable and readable.
At 41 tools, the surface area is very large for a single MCP server and exceeds the 'heavy' threshold. While each tool serves a distinct purpose, the sheer number makes the server feel bloated and harder to navigate; many tools could be grouped or pruned without losing core functionality.
The server covers a broad domain: content read/list, personas, skills management, vault CRUD (except update/delete intentionally), provenance, licensing, memory, and async question/narada workflows. Minor gaps exist like no tool to cancel a narada job or update a memory, but these are workable and the core workflows are well supported.