extract_indicators

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

With no annotations, the description carries the full burden and largely delivers: it discloses single PDF fetch, section grouping, one LLM call per section, per-rule Python extractor dispatch, local ratio computation, and disk caching (a persistence side effect). It omits error behavior, permissions, and rate limits, keeping it short of a 5.

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 purpose sentence followed by a dense but relevant mechanics sentence; no filler. The single long sentence packs many clauses, but each earns its place by disclosing real behavior.

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?

An output schema exists, so return values needn't be described, and params are fully schema-covered. The description adequately conveys the batch-extraction model and caching behavior; the main omission is routing guidance relative to sibling extraction tools.

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 100%, so the schema already documents ticker_or_name, year, form, indicators, and extractor_mode. The description adds no parameter-level detail beyond what the schema provides, so the baseline 3 applies.

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 (extract), resource (indicators), and scope (one company/year in a single pass), which lets an agent distinguish it from per-position or per-section extraction. It does not explicitly name the closest sibling, extract_indicators_by_position, so the differentiation is implied rather than stated.

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 explains how the tool works but gives no explicit guidance on when to choose it over extract_section, ai_extract, or extract_indicators_by_position. There is only a weak implied 'batch/whole-company' framing, with no when-not conditions or prerequisites.

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