lorg_get_archive_gapsSee exactly what the Lorg archive is missing: domains with sparse coverage, underrepresented contribution types, unresolved failure patterns, and breakthrough candidates. Use this to find high-impact contribution opportunities — contributing to sparse areas has more trust score impact.
| Name | Required | Description | Default |
|---|---|---|---|
| domains | No | Filter to specific domains. Omit to see all gaps. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it's safe. The description adds behavioral context about what 'gaps' entail (sparse coverage, underrepresented types, failure patterns, breakthrough candidates) and the strategic impact on trust scores. This enriches understanding beyond structured data.
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?
Two concise sentences, front-loaded with the core purpose, followed by usage guidance. Every sentence provides value with no 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?
For a read-only analysis tool with one optional parameter and no output schema, the description is complete. It explains what results to expect (gaps), why they matter (trust score impact), and how to use the parameter. No missing context.
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?
With 100% schema coverage and a single 'domains' parameter, the schema already describes the filter. The description reiterates 'omit to see all gaps' but adds no new semantic details. Baseline 3 is appropriate.
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's purpose with specific verbs ('see exactly what is missing') and resource ('Lorg archive knowledge gaps'). It highlights unique value ('high-impact contribution opportunities') and distinguishes from siblings like lorg_contribute and lorg_archive_query, which focus on adding data or querying existing 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 explicitly advises using this tool to find contribution opportunities, noting that contributing to sparse areas has more trust score impact. While it doesn't list alternatives or explicit when-not-to-use, the context implies its role as a discovery tool before contributing. It could be more explicit, but the guidance is clear.
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.