tailrisk_load_csv_series

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

Annotations declare readOnlyHint=true and idempotentHint=true, covering safety. The description adds valuable behavioral context by mentioning that non-numeric and empty cells are skipped and counted, and that truncation may occur (via the 'truncated' return field). This goes beyond what annotations provide without contradicting them.

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?

The description is two short paragraphs with a structured 'Returns' section. The main purpose is front-loaded, every sentence adds value (usage timing, data quality behavior, return format), and there is no redundancy or 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?

The description covers the return format and the skipping/truncation behavior, but with 0% schema coverage it leaves parameter semantics completely unexplained. The output schema may exist (indicated by 'has output schema: true'), which lightens the need to document return values, but the missing parameter explanations are a notable gap for a loading tool that an agent must call 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?

Schema description coverage is 0%, so the description must compensate for explaining parameters, but it does not. It never mentions 'path', 'column', or 'max_rows' by name, nor clarifies that 'column' is a header name or that 'max_rows' limits parsing. While parameter names are somewhat self-explanatory, the lack of description means an agent may misinterpret expectations, especially given the 0% coverage signal.

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 states a specific verb ('Read'), resource ('one numeric column from a local CSV'), and purpose ('so a series can be analysed'). It clearly distinguishes from sibling analysis tools by positioning itself as the loading step, and the phrase 'Call this before the analysis tools' reinforces its distinct role.

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 says 'Call this before the analysis tools when the data lives in a file rather than in the conversation', which gives clear context and implies when not to use it. However, it does not name specific alternatives or exclusions (e.g., when data is already in memory), which would have improved guidance.

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