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create_brief

Assemble an agenda brief from supplied fields and report missing required fields. Use iteratively to build schema-valid briefs and see validation errors.

Instructions

Assemble an agenda brief from supplied fields and report which required fields are still missing. Use when producing a brief inside the protocol instead of hand-building JSON: call it with whatever is known so far, read missing_required, and call again with the remaining fields. Call with no arguments to get an empty scaffold plus the required field list. evidence_mode defaults to reasoning_only. Returns the assembled brief object and its schema errors to the caller; it does not write files, retrieve sources, draft prose, or verify factual truth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scenariosNoOptional scenario objects with name, description, and indicators.
confidenceNoOptional confidence as a level string or a level/score/reasoning object.
watch_nextNoObservable indicators to monitor next. At least one is required.
bottom_lineNoOne-line decision-relevant conclusion.
what_changedNoWhat is materially different now versus the prior state.
evidence_modeNoHow the brief was sourced. Defaults to reasoning_only; set explicitly when sources were actually supplied.
signal_markersNoOptional qualifying markers that do not replace signal_classification.
why_it_mattersNoOptional consequence framing.
affected_actorsNoOptional list of actors materially affected.
main_uncertaintyNoThe premise that would most change the conclusion if false.
data_integrity_notesNoOptional surfaced concerns about prompt injection, source anomalies, or retrieval limits. Records a concern; it is not an automated trust verdict.
signal_classificationNoSignal class from agenda-brief.schema.json (for example signal, weak_signal, structural_shift). Call get_schema('agenda_brief') for the full enum.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does so thoroughly. It discloses the iterative 'missing_required' return, the evidence_mode default, the scaffold behavior, the returned schema errors, and explicit non-side-effects: no file writes, source retrieval, prose drafting, or factual verification. This is far richer than a bare mutation or read hint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a tight paragraph with no filler. Every sentence earns its place: purpose, usage loop, scaffold behavior, default, and exclusions. It is front-loaded with the core action and gives enough detail without becoming a manual.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 12 parameters, no output schema, and no annotations, the description covers all decision-relevant context: how to invoke iteratively, how to bootstrap with no arguments, what the response includes, and what the tool will not do. An agent has enough to select and call the tool correctly without further inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds value beyond the schema by specifying the evidence_mode default and the tool's missing-required reporting, which tells the agent how to use the 12 parameters iteratively rather than merely what each field means.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Assemble an agenda brief from supplied fields and report which required fields are still missing.' This clearly distinguishes it from siblings like validate_brief, which validate existing briefs, and get_schema, which returns schemas. It also states what it returns, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an explicit usage pattern: call with known fields, read missing_required, call again with remaining fields, or call with no arguments for a scaffold. It also gives a default behavior ('evidence_mode defaults to reasoning_only') and states clear when-not conditions (does not write files, retrieve sources, draft prose, or verify factual truth), so an agent knows when to avoid it.

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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