prune_context

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

With no annotations, the description bears the full burden. It discloses useful behavioral traits (token reduction, signature/dependency preservation, available output formats) but never states that this is a safe read-only extraction with no side effects, nor any performance or filesystem-access limits implied by project_root auto-detection.

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 followed by cleanly scoped Args/Returns sections; each line earns its place. Slightly padded by marketing-flavored wording ('hallucination-resistant', '>80%') that adds tone more than callable information.

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-value detail is unnecessary, and the parameter documentation is thorough for a 5-param, 0%-coverage schema. What's missing is the operational framing — when to use it and confirmation of read-only/no-side-effect behavior — which is meaningful for a tool with no annotations.

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 — and it does: every one of the five parameters is explained, including path semantics ('absolute or relative'), symbol syntax with concrete examples ('OrderService.procesar_orden'), the accepted format values ('stubs'/'turtle'/'json'/'nl' — not present as an enum in the schema), and project_root's auto-detection fallback.

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: 'Extracts a minimal... context contract for a given function or method,' and quantifies the effect ('>80%' token reduction). The term 'context contract' is jargon, but the following clauses (type signatures, dependencies across modules) make the intent concrete. It does not distinguish itself from the sibling verify_response, though that sibling is clearly unrelated.

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?

Usage is only implied — the tool is framed as an LLM-oriented context extractor, but there is no statement of when to call it versus reading the file directly, nor any preconditions or exclusions. The format/default guidance partially informs selection but is about output shape, not when-to-use.

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