Return patterns that have not been human-reviewed yet (no reviewed_by). Sorted low-confidence first, then needs_human_review flagged, then alpha. Use during Phase 3 review to pick the next pattern to examine.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the filtering condition (not human-reviewed) and sorting order, which is helpful. However, it does not discuss whether it is read-only, any potential rate limits, or how the limit parameter affects behavior—leaving gaps in transparency.
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 every word adds value. No fluff or 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?
Given the complexity is low (one optional param, no output schema), the description covers usage and sorting but omits the return structure or field details. Without an output schema, the agent lacks information on what properties the returned patterns contain, which is necessary for downstream processing.
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% and the description does not mention the 'limit' parameter at all. It provides no additional meaning beyond the raw schema, so the agent must infer parameter usage from other sources.
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 returns patterns not yet human-reviewed, specifies the sorting order (low-confidence first, then needs_human_review, then alpha), and explicitly says it's used during Phase 3 review to pick the next pattern. This is a specific verb+resource that distinguishes it from siblings like search_patterns or find_patterns_for_task.
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 gives explicit context: 'Use during Phase 3 review to pick the next pattern to examine.' This tells the agent when to use it, but it does not mention when not to use it or provide alternatives, so it falls short of a 5.
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 has a distinct purpose: finding patterns, cross-references, operational heuristics, requirements, listing, searching, and review stats. Overlap is minimal and well-differentiated by input parameters.
All tool names follow a consistent verb_noun pattern in snake_case, e.g., find_patterns_for_task, list_requirements, resolve_id. No mixing of conventions or vague verbs.
12 tools cover core operations (list, get, search, resolve, review) for the framework domain without bloat. Each tool serves a clear, non-redundant purpose.
Covers most needed operations for exploring the framework: listing suites, searching patterns, getting details, cross-references, review stats. Lacks a direct 'list all patterns' tool, but list_requirements and search_patterns partially fill that gap.
