faf_read
Parse a .faf and return its normalized structure (Rust→WASM, at the edge).
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | Raw .faf file content (YAML) |
rust-faf-mcp
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It mentions 'normalized structure' but does not discuss side effects, performance, error behavior, or safety. The parse operation is likely read-only but unstated.
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?
The description is very short (one sentence) with no wasted words. However, it includes the parenthetical '(Rust→WASM, at the edge)' which is not essential for understanding the tool's function.
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?
Since no output schema exists, the description should elaborate on the return value beyond 'normalized structure'. It lacks details on error handling, encoding, or the structure format, making it incomplete for a parsing tool.
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% and the single parameter 'content' is described. The tool description adds no extra meaning beyond the schema's 'Raw .faf file content (YAML)'.
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 states it parses a .faf file and returns a normalized structure, clearly indicating the verb and resource. It distinguishes from siblings (faf_score, faf_validate) by implying different functions, but the technology detail (Rust→WASM) is not essential for tool selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like faf_score or faf_validate. The description does not mention prerequisites, when-not-to-use, or context for invocation.
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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TDQS
A3.6/5.0
Disambiguation5/5
Each tool has a clearly distinct purpose: reading/normalizing, scoring completeness, and validating with errors/warnings. Even though faf_score and faf_validate both return a score, the validation adds diagnostic information, reducing overlap.
Naming Consistency5/5
All three tools follow a consistent faf_verb pattern using snake_case, with verbs 'read', 'score', and 'validate'. No mixing of conventions or unclear names.
Tool Count5/5
Three tools is a well-scoped set for a specialized server handling .faf files. It covers essential operations without being bloated or insufficient for the niche domain.
Completeness4/5
The server covers reading, scoring, and validating .faf files, which are key analysis operations. However, it lacks tools for creating, writing, or modifying .faf files, which may be a gap depending on use case.