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yoloshii

gigaxity-deep-research

by yoloshii

synthesize

Synthesize pre-gathered content into coherent analysis with citations, directed by a specific query.

Instructions

Synthesize pre-gathered content into coherent analysis.

Use when you already have sources from other tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSynthesis focus/question
styleNoOutput format/length. When None and a preset is provided, the preset's own style is used (preset wins by default; explicit style always overrides). When None and no preset, defaults to comprehensive.
presetNoProcessing pipeline preset (comprehensive, fast, contracrow, academic, tutorial)
sourcesYesPre-gathered source documents with title, content, url, origin, source_type
gate_focusNoOptional focus string the pre-synthesis relevance gate scores sources against instead of the full query (Q2 precision lever for verbose queries). Omitted/None/whitespace uses the full query.
openrouter_api_keyNoPer-request key override; defaults to RESEARCH_LLM_API_KEY.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states the purpose without detailing side effects, safety, or any behavioral traits. For instance, it doesn't indicate whether the tool is read-only, whether it modifies any state, or what the synthesis process entails (e.g., uses LLM calls). This is a significant gap.

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?

The description is extremely concise at two sentences. The first sentence captures the primary purpose, and the second provides direct usage context. Every word is earned; no fluff.

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

Completeness3/5

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

Given the complexity (6 parameters, output schema exists) and lack of annotations, the description is minimal. The output schema covers return values, so that's not an issue. However, the description does not explain the synthesis process, any prerequisites (other than having sources), or how to handle the output. It is adequate but lacks depth in behavioral context.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema itself fully documents the parameters. The tool description does not add any additional meaning beyond what the schema already provides. Thus, the baseline score of 3 is appropriate.

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?

The description clearly states the tool's action ('Synthesize pre-gathered content') and outcome ('into coherent analysis'). It distinguishes from sibling tools by explicitly mentioning that it works with already-gathered sources, which sets it apart from search or discover.

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

Usage Guidelines4/5

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

The description provides explicit guidance: 'Use when you already have sources from other tools.' This tells the agent when to invoke it, but it doesn't explicitly mention when not to use it or provide alternatives. Given the sibling tools, the guidance is sufficient but could be more comprehensive.

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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