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rewrite_for_geo

Rewrites content for AI answer synthesis engines by enriching entities and framing comparisons, making it more likely to be cited in multi-source summaries.

Instructions

Rewrite a content block for Generative Engine Optimization: entity-rich, comparison-ready, synthesis-friendly. Tuned for surfaces that summarize across sources (Perplexity, Google AI Mode, Claude search).

Read-only on input. Does NOT write back to the source URL - returns the rewritten content as a string.

This tool delegates the actual rewrite to the calling LLM via MCP sampling - it does not call any external API itself. The MCP host's model produces the rewrite. Output may vary across runs (model-dependent).

When to use: optimizing for synthesis-style answers across multiple sources. For direct-answer (BLUF + FAQ) optimization on a single page, use rewrite_for_aeo instead.

Either url or text must be provided. target_query is required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoPublic URL whose content should be fetched and rewritten. Either this OR `text` is required.
textNoRaw content to rewrite directly. Either this OR `url` is required.
target_queryYesThe user query the rewrite should answer. Required - drives entity selection and comparison framing.
add_comparison_tableNoIf true, inject an explicit X-vs-Y comparison table into the rewrite (useful for `X vs Y` queries). Default false.
max_wordsNoSoft word budget. Default 1500. Range 100-5000.
respect_robotsNoIf true (default), respect robots.txt when fetching `url`. Ignored when `text` is used.
Behavior5/5

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

No annotations provided. Description fully compensates by explaining the tool is read-only, delegates rewriting to the LLM via MCP sampling (no external API), and that output may vary across runs. Covers all behavioral aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured, front-loaded with purpose, then behavioral caveats, usage guidelines, and parameter hints. Every sentence adds value, no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters (all described in schema) and no output schema, description covers purpose, usage, behavioral details, parameter interplay, and output format ('returns string'). Completely adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions, earning baseline of 3. Description adds value by clarifying the either/or requirement for url and text, explaining target_query drives entity selection, and noting when add_comparison_table is useful.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it rewrites content for Generative Engine Optimization with specific traits (entity-rich, comparison-ready, synthesis-friendly). It distinguishes from sibling 'rewrite_for_aeo' by noting different optimization goals (synthesis vs direct-answer).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use this tool (optimizing for synthesis-style answers across multiple sources) and when to use the alternative 'rewrite_for_aeo' (direct-answer optimization). Also clarifies it does not write back to source.

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

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