india_threat_scorecardAggregate counts of publicly observed cyber threat activity affecting Indian organisations, by industry vertical and category, for one edition (latest by default). Aggregate only: no organisation is named. A vertical the source did not cover is unmeasured, not zero.
| Name | Required | Description | Default |
|---|---|---|---|
| edition | No | Edition slug, YYYY-MM. Omit for the latest. |
Changes observed during successful MCP inspections.
Input schema / properties / edition / enumPrevious value: -[
- "2026-08"
-]New value: +[
+ "2026-09",
+ "2026-08"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful behavioural context beyond that: results are aggregate only, no organisation is named, and an uncovered vertical is 'unmeasured, not zero' — a data-interpretation caveat an agent could not infer from 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?
Three tight sentences, front-loaded with what is returned and how it is scoped, followed by the aggregate-only caveat and the unmeasured-not-zero clarification. No sentence is filler.
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?
With no output schema, the description carries the burden of describing returns, and it does so adequately: aggregate counts by vertical and category, per edition, anonymised. The only residual gap is that it doesn't indicate result shape beyond 'counts', but for a single-parameter read tool this is close to complete.
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% and the single enum parameter is fully documented in the schema with its YYYY-MM format and omit-for-latest behaviour. The description adds no syntax beyond what the schema already provides, so the baseline of 3 applies.
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?
States a specific verb (aggregate) plus resource (publicly observed cyber threat activity affecting Indian organisations) and the dimensions of aggregation (industry vertical and category). It is unmistakably distinct from the sibling tools, which all deal with regulations and reporting deadlines rather than threat counts.
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 makes the selection context explicit — one edition, latest by default — which tells the agent how to invoke it correctly. It does not name an alternative tool or state when to prefer a sibling, so it stops short of the top score.
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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