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

No annotations exist, so the description carries the full behavioral burden. It usefully discloses the result range (1–5) and the evaluation criteria, which is genuine context beyond the schema. It is silent, however, on whether the score is returned as a single number or a per-criterion breakdown, on error behavior for an invalid ticker, and on any latency or cost.

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?

Two short sentences with no filler; the purpose is front-loaded and the rubric follows. Slightly terse for a tool with no annotations or output schema, but nothing is wasted.

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?

For a single-parameter analytic tool with no output schema, the description covers what is measured and the output scale, which is the core need. It leaves open the shape of the response (single score vs. criterion breakdown) and any failure modes, so it is adequate rather than complete.

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% and the single parameter 'symbol' is already documented as a ticker with an example (AAPL). The description adds no parameter-level meaning beyond that. Baseline 3 applies when the schema does the heavy lifting.

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 and resource ('Évalue la qualité du management d'une entreprise') and quantifies the output scale (1 à 5). The rubric criteria (track record, allocation du capital, communication, alignement actionnaires) sharpen what is being measured. It does not explicitly distinguish itself from the close sibling get_moat_score, which keeps it from a 5.

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?

No indication of when to reach for this tool versus get_moat_score, get_intrinsic_value, or the general analyze_stock. There are no prerequisites, no exclusions, and no sequencing guidance. The agent must infer usage purely from the tool name.

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