Return methodology documentation for a Scrutica metric or index. Topics: 'flop-estimation', 'cost-index', 'compute-visibility-index', 'supply-chain-weighting', 'chokepoint-cascade', 'sovereign-execution-classification'. Returns the canonical URL + section anchor + summary. Use this when a user asks "how did you calculate X".
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
ReadOnlyHint is true, and the description adds valuable detail about the return shape (canonical URL + section anchor + summary). This exceeds the annotation's simple safety signal, though it doesn't describe edge cases or additional behavior.
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 compact and front-loaded: purpose in the first sentence, topics in the second, and return/usage in the third. No filler words, and every sentence adds distinct 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 one-parameter tool with a clear enum and a read-only action, the description covers purpose, usage trigger, topic list, and return format. Even without an output schema, the agent knows what to expect. It is complete for the tool's simplicity.
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 0%, so the description must compensate. It does by listing all enum values in prose and explaining that the topic refers to a 'metric or index,' which adds context beyond the bare enum. Given the single parameter's simplicity, this is sufficient.
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 opens with a specific verb+resource: 'Return methodology documentation for a Scrutica metric or index.' It clearly distinguishes this from sibling tools focused on entities, scenarios, or searches. The explicit list of topics further clarifies scope.
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 an explicit when-to-use instruction: 'Use this when a user asks "how did you calculate X".' However, it does not mention when not to use it or name alternative tools, so it falls short of a full 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 targets a clearly distinct resource or action: canonical entity/facility/program lookups, free-text search, supply-chain traversal, BIS query versus BIS change-log, FLOP estimation, and methodology docs. Cross-references explicitly redirect likely-confused intents, such as using scrutica_query_export_controls for entity designations and scrutica_entity_list_changes for changes, so misselection is unlikely.
The naming is mostly consistent: scrutica_get_* for canonical lookups, plus clear action-style names like scrutica_search, scrutica_query_export_controls, and scrutica_estimate_flops. The main deviation is scrutica_entity_list_changes, which reads as a noun phrase rather than a verb-first tool name, so the pattern is coherent but not perfectly uniform.
Ten tools is well calibrated for this server's broad but focused domain coverage. Each meaningful data area gets one or two dedicated tools—companies, facilities, sovereign programs, supply chain, export controls, scenarios, methodology, and FLOP estimation—with no count-inflating duplicates.
The read-side surface is largely complete: search, get-by-ID, change-tracking, relationship traversal, scenario retrieval, and methodology lookup all exist. The main gap is that some methodology topics describe metrics or indices—such as cost-index and compute-visibility index—without an obvious dedicated tool for retrieving those metric values directly.
