Skip to main content
Glama

optidev_implementation_guide

Analyzes Jira ticket content and optional project context to provide complete implementation guidance for Optimizely development.

Instructions

Analyzes Jira tickets and provides complete implementation guidance

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ticketContentYesJira ticket content or requirements text
projectContextNoOptional project context or existing codebase information
Behavior2/5

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

No annotations are present, so the description must carry the full burden of behavioral disclosure. It states 'analyzes' and 'provides guidance,' but does not disclose whether the tool has side effects, requires authentication, or what the output format is. The word 'complete' overpromises without specifying boundaries, leaving the agent uncertain about the actual behavior.

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 a single, front-loaded sentence: 'Analyzes Jira tickets and provides complete implementation guidance.' There is zero wasted text, and it immediately communicates the core function. It is appropriately sized for the tool's apparent simplicity.

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

Completeness2/5

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

Given 2 parameters, no output schema, and no annotations, the description is too sparse to be complete. It does not explain what 'complete implementation guidance' includes, what the output looks like, or how this tool differs from the sibling tools. The schema helps with parameters, but the overall behavior remains underspecified.

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?

The schema descriptions cover 100% of parameters (ticketContent and projectContext) with clear explanations. The tool description adds no additional meaning beyond the schema, so a baseline score of 3 is appropriate.

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

Purpose4/5

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

The description clearly states the tool analyzes Jira tickets and provides implementation guidance, which specifies the resource (Jira tickets) and the outcome (guidance). It is distinct from sibling tools like debug_helper or code_analyzer, though it doesn't explicitly name them.

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

Usage Guidelines3/5

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

The usage context is implied: use when you have Jira tickets and need implementation guidance. However, there is no explicit when-not-to-use, no comparison to alternatives, and no mention of prerequisites (e.g., Is projectContext required?). This is typical of a tool with implied usage.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/biswajitpanday/Optivise'

If you have feedback or need assistance with the MCP directory API, please join our Discord server