Skip to main content
Glama

save_task_analysis

Record codebase analysis results, including dependencies, risks, and recommendations, to generate an enriched execution prompt with next steps.

Instructions

Saves the codebase analysis performed by Claude Code. Call this after analyzing the codebase following the prepare_task_for_execution prompt. Records dependencies, risks, and recommendations. ⚠️ IMPORTANT: The response includes nextSteps guidance - follow it to get the enriched execution prompt with all context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskIdYesTask ID
analysisYesAnalysis results from codebase inspection
Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses key behavioral aspects: the tool records dependencies, risks, and recommendations, and importantly, the response includes 'nextSteps guidance' that should be followed. This goes beyond the schema, though it doesn't describe side effects like overwrites or appending 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 three clear, information-dense sentences. It front-loads the core purpose, then provides the usage trigger and a critical warning about nextSteps. Every sentence earns its place with no redundancy or fluff.

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

Completeness4/5

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

The tool has nested parameters and no output schema, but the description covers the essential context: when to call it, what data it records, and that the response includes nextSteps guidance. It doesn't detail the full return structure, but for a save operation, this is reasonably complete, given the rich schema and usage instruction.

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% (taskId: 'Task ID', analysis: 'Analysis results from codebase inspection'). The description mentions recording dependencies, risks, and recommendations, which maps to the schema's nested properties but doesn't add new parameter-level meaning beyond what the schema already provides. Baseline 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 purpose: 'Saves the codebase analysis performed by Claude Code.' It names a specific action (save) and resource (codebase analysis), and distinguishes itself from sibling tools like save_dependencies and save_story_decomposition by focusing on task analysis.

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 clear usage context: 'Call this after analyzing the codebase following the prepare_task_for_execution prompt.' This tells the agent when to use it. It doesn't explicitly mention alternatives or when not to use it, but the context is sufficient for a 4 scoring.

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/khaoss85/mcp-orchestro'

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