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faf_auto

Runs the full setup pipeline in one call: init or merge, stack detection, CLAUDE.md generation, and scoring, returning a final AI-readiness score and created files.

Instructions

Run the setup pipeline in one call — init or merge, stack detection, CLAUDE.md, and score — taking a project from no context to a scored project.faf plus CLAUDE.md; faf_go closes the human slots. Returns the final AI-readiness score and what was created. Use this as the fast path on a fresh project; use the individual tools when you need finer control.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoProject path. Sets session context for subsequent calls.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.3.2
    • removedInput schema / properties / force
      Removed value: -{
      -  "description": "Force overwrite existing files",
      -  "type": "boolean"
      -}
  2. First observedv2.1.1

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false and openWorldHint=false, so the write/scope profile is covered. The description usefully adds what the tool creates (project.faf and CLAUDE.md) and that it returns the final AI-readiness score. It does not say whether existing files are overwritten versus merged, or how the 'init or merge' branch is chosen — meaningful gaps for a mutating orchestrator.

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

Conciseness4/5

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

Front-loaded with the action sentence, then return value, then routing guidance — a sound order. The pipeline enumeration clause is dense with em-dashes and parentheses but each sentence carries distinct information, so little is wasted.

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?

With no output schema, the description compensates by stating the return ('final AI-readiness score and what was created') and the artifacts produced. It is nearly complete for an orchestration tool; only the init-vs-merge decision rule and overwrite behavior for existing files are missing.

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% for the single 'path' parameter, and the schema documents its session-context side effect. The description adds nothing about the parameter, so the baseline of 3 applies for a fully documented one-param tool.

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?

Specific verb and resource ('run the setup pipeline in one call') with an explicit enumeration of the stages it chains (init/merge, stack detection, CLAUDE.md, score). It also names the sibling it complements (faf_go) and the alternative class (the individual tools), so an agent can place it without opening any schema.

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?

Explicit routing: 'Use this as the fast path on a fresh project; use the individual tools when you need finer control.' It states both the condition that selects this tool and the condition that selects alternatives, plus where faf_go fits after it.

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