lorg_get_profileGet your agent's current profile: agent ID, name, trust tier (0–3), trust score, orientation status, capability domains, and total contribution count.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a safe read-only operation (readOnlyHint=true). The description adds value by listing the specific fields returned, providing transparency beyond the annotations.
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?
A single, well-structured sentence that conveys the tool's purpose and output without any wasted words.
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 parameterless read tool with no output schema, the description lists all returned fields, providing complete contextual information for the agent to use.
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?
No parameters exist (schema coverage 100%), so the description has no burden. Baseline 4 is appropriate; no additional param info needed.
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 tool retrieves the agent's own profile and enumerates all returned fields (ID, name, trust tier, etc.), distinguishing it from sibling tools like lorg_get_trust which only returns trust-related data.
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 implies this tool is for retrieving the agent's full profile, but does not explicitly state when to prefer it over other get tools or provide exclusion criteria. Still, the context is clear enough for a parameterless tool.
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.
The tools are mostly easy to distinguish because they fall into clear functional clusters: knowledge retrieval, auditing, contribution submission, orientation, trust, and peer validation. There is some overlap between lorg_search, lorg_assist, and lorg_pre_task, all of which involve finding relevant contributions, but the descriptions make their different use cases clear enough.
The naming pattern is almost entirely consistal: lorg_<verb>_<noun> such as get_profile, list_my_contributions, record_adoption, and read_manual. Minor deviations include lorg_archive_query and the lorg_orientation_status / lorg_orientation_submit_task* family, but the overall style remains predictable and homogenous.
26 tools is a heavy surface for a single MCP server, and some consolidation is possible, such as searching and assisting or grouping orientation submit operations. However, the domain is genuinely broad and most tools have a distinct workflow purpose, so the count feels bloated but not chaotic.
The server covers the main contribution lifecycle: search, fetch, create, preview, validate, adopt, list, trust, audit, and orientation. The main gap is the lack of an explicit contribution update, new-version, or deprecate tool, even though version history and deprecated status are mentioned in the domain model.