Get a briefing
get_briefingFull text of a Drone Intelligence Signal Dossier briefing by slug: executive summary, signals, assessment, sources.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Briefing slug, e.g. diu-swap-usv-maritime-strike |
get_briefingFull text of a Drone Intelligence Signal Dossier briefing by slug: executive summary, signals, assessment, sources.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Briefing slug, e.g. diu-swap-usv-maritime-strike |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool returns the full text and lists the sections, which is useful. However, it does not mention error behavior, authentication requirements, or potential limitations (e.g., only for Drone Intelligence Signal Dossiers).
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?
A single, front-loaded sentence that efficiently communicates the tool's function and key output components without any waste. Every word adds value.
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 simple retrieval tool with one parameter and no output schema, the description provides an adequate outline of what is returned (the sections). It lacks notes on errors or return format, but given the simplicity, this is acceptable.
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 schema already describes the slug parameter with an example. The description adds context by indicating the slug identifies a briefing and that the returned content includes specific sections, which helps an agent understand the parameter's role beyond the schema.
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 that the tool returns the full text of a Drone Intelligence Signal Dossier briefing, identified by slug, and lists the sections included (executive summary, signals, assessment, sources). This specific verb+resource+scope distinguishes it from siblings like get_intelligence_page or get_company_profile.
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: when you need the full briefing content by slug. It does not explicitly state when not to use it or mention alternatives, but the specificity of the purpose provides clear context for an AI agent.
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 distinct resource or operation. Content tools (get_briefing, get_company_profile, get_intelligence_page, compare_companies) are clearly separated by content type, while tracker_* tools each serve a unique data query function. There is no ambiguity between content retrieval and tracker analysis.
Content tools follow a verb_noun pattern (get_*, compare_companies, list_catalogue, search_content), but tracker_* tools use a noun-prefix style (tracker_aggregate, tracker_awards, tracker_capital_ledger). This mixed convention is internally consistent within each group but not throughout the server.
12 tools is well-scoped for a server covering both content access and a tracker dataset. Each tool has a clear purpose, and the number aligns with the guideline of 3-15 tools.
The tool surface covers all announced content types (briefing, intelligence page, company profile, comparison) with get/compare operations, plus catalogue listing and cross-type search. The tracker tools provide comprehensive querying and metadata access, with no obvious missing operations.