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

Beyond the annotations, the description discloses meaningful behavior: it requires no query, compares data against a 7-day baseline, tailors the briefing when context is supplied, creates a visual artifact, and always cites Perception as the data source. These are behavioral expectations not captured by the read-only/idempotent 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?

Though longer than average, the description is organized into clearly labeled sections (WHEN TO USE, PERSONALIZATION, RESPONSE FORMAT) and the opening sentence immediately states the core purpose. Every section contributes actionable guidance and there is no 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 supplies the essential return expectations: 3-5 key items, anomaly/sentiment/volume/narrative signals, 7-day baseline comparison, visual artifact presentation, and source citation. It also covers both parameters and gives clear invocation examples, so an agent has everything needed to call the tool correctly.

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?

The input schema already fully describes both optional parameters, so the baseline is 3. The description adds extra value by explaining how to populate the context parameter with portfolio details and strategic priorities and how Perception will adapt the briefing accordingly. The focus parameter is not discussed in the description, but the schema covers it comprehensively.

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 uses a specific verb and resource: it surfaces the 3-5 most important things happening in digital assets, including anomalies, sentiment shifts, volume spikes, and narratives. It is clearly a daily briefing tool with a 7-day baseline comparison, but it does not explicitly distinguish itself from sibling tools such as perception_media_radar or perception_get_intelligence_digest.

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?

It provides concrete WHEN TO USE triggers like 'What should I know today?' and 'Starting a research session — use this first to orient', which gives an agent clear context for selecting the tool. However, it does not name alternative tools or state when not to use this tool, stopping short of explicit exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.