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optidev_context_analyzer

Identifies Optimizely context in developer prompts and delivers curated, AI-scored information to LLMs via vector search.

Instructions

Enhanced context analysis with AI-powered relevance scoring and vector search

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesUser prompt to analyze for Optimizely context
enableAINoEnable AI-powered features (requires API keys)
ideRulesNoOptional IDE rules for context enhancement
projectPathNoOptional project path for IDE context
Behavior2/5

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

With no annotations, the description carries the burden of behavioral disclosure, but it only mentions AI-powered relevance scoring and vector search. It doesn't disclose safety (read-only vs. mutating), API key requirements, side effects, or what happens when enableAI is false.

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

Conciseness3/5

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

The description is short and front-loaded as a noun phrase, but it's under-specified and doesn't state the action verb. It's concise but not structured in a way that clearly communicates the tool's function.

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

Completeness1/5

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

For a tool with 4 parameters, no output schema, and no annotations, the description is completely inadequate. It doesn't explain what the tool does with the prompt, expected output, or any prerequisites, making it insufficient for an agent to use correctly.

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 coverage is 100% with descriptions for all 4 parameters, so baseline is 3. The description adds no parameter-specific meaning beyond what the schema already provides, but no compensation is needed.

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

Purpose3/5

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

The description says 'Enhanced context analysis with AI-powered relevance scoring and vector search,' indicating it analyzes context and adds AI features, but it lacks a specific verb+resource and doesn't mention that the context is for Optimizely. It also doesn't distinguish this from sibling tools like optidev_code_analyzer.

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

Usage Guidelines1/5

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

No guidance is given on when to use this tool versus alternatives. The description doesn't mention prerequisites, alternatives, or any use-case context, leaving the agent without a basis for selection.

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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