root_punto_fijo

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

With no annotations provided, the description does real work: it discloses the convergence criterion, the Lipschitz check, the iteration table, the convergence flag, and the special return shape when plot=True. It could still say more about behavior when convergence fails or when g_str is invalid, but the key operational traits are covered.

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 front-loaded with purpose and convergence condition, then uses compact Args and Returns sections. Every sentence adds useful information for invoking the tool correctly.

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 six-parameter numerical tool with no annotations and no output schema, the description is largely complete: it explains the method, convergence condition, parameters, and return structure including the plot case. Minor gaps remain around error behavior and exact iteration-table format, but the essential context is present.

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 carry the burden. It meaningfully documents all six parameters: g_str as the iteration expression, x0 as the initial guess, tol as tolerance, max_iter as iteration cap, precision as rounding digits, and plot as PNG-returning flag. It does not specify the expression syntax for g_str, which keeps it from a 5.

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 names a specific numerical method and states the exact problem it solves: finding a fixed point of g(x)=x using fixed-point iteration. It is clear enough to distinguish from general root-finding siblings by method, though it does not explicitly contrast itself with root_bisection, root_newton_raphson, or root_aitken.

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 gives the mathematical applicability condition 'Converges when |g'(x)| < 1 near the root', which implies when the method is appropriate. However, it never explicitly says when to choose this method over sibling root-finding tools or what to do if the convergence condition fails.

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