arm-migrate-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: analyze workloads, fetch results, generate migration plans, and trigger benchmarks. No overlap or ambiguity.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern (analyze_workload, fetch_benchmark_results, generate_migration_plan, trigger_benchmark).
Tool Count5/5With 4 tools, the set covers the core migration workflow without being over- or under-scoped. Each tool earns its place.
Completeness5/5The tool surface covers the full migration lifecycle: analyze current workload, benchmark performance, generate migration plan, and trigger benchmarks. No obvious gaps.
Average 3.6/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states artifacts are 'ready-to-commit' but does not disclose side effects, permissions, or whether it modifies state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence efficiently conveys the tool's purpose and outputs. Could be slightly clearer by breaking into separate points.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, yet description does not explain return format or how artifacts are provided. Missing guidance on optional parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 67% of parameters with descriptions. The description adds no extra semantic beyond the schema for the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: generating Arm64 migration artifacts including Dockerfile, CI workflow, build flags, and checklist. It distinguishes from siblings which focus on analysis or benchmarking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (for Arm64 migration planning) but does not explicitly contrast with sibling tools or state prerequisites or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only mentions download and return. Does not disclose authentication needs, rate limits, error handling (e.g., if run incomplete or missing), or whether artifacts are deleted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no filler. Front-loaded with key action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema; description mentions 'migration report with tokens/sec deltas' but not format or structure. Lacks details on error conditions or prerequisites.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters (100% coverage). Description adds 'completed' qualification for run_id and restates schema info, but adds no meaningful extra beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Explicitly states verb 'Download', resource 'artifacts from completed arm-bench run', and output 'migration report with tokens/sec deltas'. Distinct from sibling tools that analyze workloads or plan migrations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicitly suggests use after a completed run, but no explicit 'when to use' or 'when not to use' guidance. No mention of alternatives like analyzing workload instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the requirement for an authenticated gh CLI and the fallback to manual instructions, but omits details about what happens after dispatch (e.g., async behavior, response, error handling). Some behavioral insight is provided, but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that immediately conveys the tool's primary function. Every word adds value; there is no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description is not required to explain return values. However, for a workflow trigger tool, it lacks information about expected outcomes (e.g., job URL, status) and how it fits into the pipeline with sibling tools (e.g., use after trigger). It is adequate but not fully complete for an AI agent's decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage: both parameters have descriptions. The tool's description adds context about the workflow (e.g., benchmark matrix) but does not enhance understanding of the parameters beyond what the schema already provides. Baseline score 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (trigger), the specific workflow (arm-bench with benchmark matrix), and the target (GitHub repo via workflow_dispatch). It distinguishes from sibling tools by focusing on triggering a workflow, which is unique among them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions a prerequisite (authenticated gh CLI) and a fallback (manual instructions), but does not explicitly state when to use this tool versus its siblings. The usage context is implied by the tool's purpose, but no exclusion criteria or alternative selection guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses the output format (severity-ranked signals with fixes) and implies read-only analysis without side effects. However, it does not detail potential rate limits or authentication requirements, but the core behavior is well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, densely packed sentence that front-loads the purpose and scope. Every word adds value, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 4 optional parameters and no output schema, the description adequately explains the tool's function and output. It lacks details on handling multiple inputs or response format specifics, but is sufficient for an experienced user.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptive parameter names and descriptions. The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes LLM workloads for Arm64 migration blockers and optimization, specifying input types (Dockerfile, compose, packages, description). It distinguishes from siblings like fetch_benchmark_results or generate_migration_plan which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when analyzing workloads but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it. No comparison with sibling tools is given.
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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