get_digest

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

With no annotations, the description carries the burden and does well: it discloses latency (20-90 seconds) and a real cost (AI provider tokens), which are the traits that actually affect an agent's decision to call it. It stops short of stating auth requirements or whether the generated digest is persisted, so it is strong but not exhaustive.

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?

Front-loaded with the action, then cost/latency context, then the routing alternative, then the argument. Every sentence carries decision-relevant information and the Args block is compact.

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?

Output schema exists, so return values need no explanation. For a single-optional-param tool the description covers action, cost, latency, alternative selection and parameter bounds — nothing an agent needs to invoke it correctly is missing.

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% (the schema only carries type and default), so the description must compensate, and it does: 'hours: How many hours back to look, 1 to 168 (default 24)' supplies the unit, meaning and a range constraint absent from 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?

States a specific verb+resource ('Generate a fresh digest of the configured Telegram channels') and elaborates the pipeline (collect, AI-summarize, format). The word 'fresh' implicitly separates it from the sibling get_last_digest, so an agent can route without opening a schema.

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?

Explicitly routes: 'prefer get_last_digest when recent data is enough', and gives a concrete configuration hint ('Use hours=168 for a weekly digest'). Both the alternative and the selecting condition are stated, not left to inference.

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