faf_score
Score a .faf — 0-100 completeness (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
B3.4/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description fails to disclose side effects, mutability, or constraints like idempotency or rate limits. 'Score' suggests a safe computation, but no confirmation.
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?
Single, front-loaded sentence with no waste. Efficiently communicates core purpose and context.
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?
Missing behavioral details, usage scenarios, and return format; with no output schema nor annotations, description is insufficient for a standalone 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 100%; parameter 'content' already described as 'Raw .faf file content (YAML)' in schema. Description adds no additional meaning beyond the schema.
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?
Clearly states verb 'Score' and resource '.faf' with specific output range '0-100 completeness' and context 'Rust→WASM, at the edge', distinguishing from sibling tools read/validate.
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?
No explicit when-to-use or alternatives provided; usage is implied but not contrasted with sibling tools or edge cases.
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.