subjectsNavigate the SiStat table tree. Nodes are folders (type "l") or tables (type "t", id ends in ".px"). Root lists tables directly.
| Name | Required | Description | Default |
|---|---|---|---|
| path | No | Sub-path under /Data/ (default empty = root). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond the annotations by explaining the folder/table distinction and root behavior. It does not contradict the read-only, idempotent, or non-destructive hints. However, it does not mention edge cases or limitations.
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 concise sentences, front-loaded with the primary purpose in the first sentence. Every word adds value, and there is no unnecessary repetition or verbosity.
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?
The description adequately explains the tool's function for navigating the tree, but without an output schema, it lacks detail on the exact return format. The provided type hints partially compensate, but a more explicit description of the output structure would improve completeness.
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 coverage is 100% for the single 'path' parameter, which already describes its purpose. The tool description does not add any additional meaning or usage details for the parameter beyond what the schema provides.
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 is for navigating the SiStat table tree, specifies nodes as folders or tables with type indicators, and explicitly mentions the root behavior. This distinguishes it from potential sibling tools and provides a precise verb-resource pair.
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 usage for navigating the tree but does not explicitly state when to use this tool versus alternatives like query_table or table_meta. No exclusion criteria or comparison to siblings is provided, relying on the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most tools have clearly distinct purposes, but there is some overlap among ask_pipeworx, ask_pipeworx_grounded, and deep_research, as well as between discover_tools and suggest_questions. However, detailed descriptions help differentiate them.
Naming conventions are highly inconsistent, mixing snake_case (ask_pipeworx, forget), camelCase (discoverTools, suggestQuestions), and underscores (ai_visibility_check, compare_entities). No predictable pattern.
33 tools is on the high side, but the broad domain (finance, pharma, prediction markets, etc.) partly justifies it. However, some tools like forget, remember, recall seem generic and could be separated.
The tool surface covers a wide range of functionalities: visibility checks, pipeworx queries, entity profiles, comparisons, subscriptions, memory, and more. Minor gaps may exist in real-time data or specific niche sources.