mcp-rap-migrator

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct step in the migration workflow: analysis, CDS checking, transport creation, skeleton generation, human checkpoint, writing objects, and validation. No overlap or ambiguity.
Naming Consistency4/5
Most tool names follow a verb_noun pattern (analyze_module_pool, check_released_cds, create_transport, generate_rap_skeleton, write_abap_object). However, 'human_checkpoint' is noun_noun and 'validate_and_activate' uses two verbs, breaking the pattern slightly.
Tool Count5/5
7 tools cover the entire migration pipeline without being excessive. Each tool serves a necessary function, and the count is appropriate for the domain's complexity.
Completeness5/5
The tool set covers all essential steps from analysis through activation, including mandatory checkpoints. No obvious gaps for a migration workflow.
Average 4.2/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 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
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. States it runs syntax check first and returns errors for the agent to fix before activation, but does not clarify the exact outcome on success (e.g., what is returned after activation), whether activation is atomic, or if partial activation occurs. Missing output schema increases need for transparency.
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?
Extremely concise: two sentences that front-load the step number, purpose, and key behavioral info. Every sentence adds value with no wasted words.
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?
No output schema and description does not explain return values for success, only mentions error returns. Does not specify whether activation is atomic or partial, nor how this integrates with sibling tools like check_released_cds. Lacks sufficient detail for an activation tool in a workflow.
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?
Only one parameter ('objects') with 100% schema coverage, so baseline is 3. Tool description adds no extra meaning beyond the schema's 'List of {type, name} to activate in order' – does not specify valid types or provide additional usage hints.
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 it activates ABAP objects via ADT REST, is STEP 4 of a workflow, runs syntax check first, and returns errors. Distinguishes it from siblings like analyze_module_pool (analysis), check_released_cds (checking), create_transport (transport creation), generate_rap_skeleton (code generation), human_checkpoint (checkpoint), and write_abap_object (writing).
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?
Explicitly indicates it's STEP 4, implying sequence, and instructs to call human_checkpoint with results. Provides clear context for use but does not explicitly mention when not to use or alternatives, though step numbering implies prerequisite steps.
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?
No annotations are provided, so the description carries the burden. It mentions that the tool returns a transport number, which is a behavioral detail. However, it does not disclose any side effects, authentication needs, or error conditions. The sequencing hint adds some value.
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 concise with two sentences, front-loading the purpose and usage guidance, then indicating the return value. No unnecessary words or repetition.
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?
For a creation tool with two parameters and no output schema, the description covers the essential purpose, sequencing, and return value. It does not mention error handling or prerequisites beyond the sequencing, but it is adequate given the tool's simplicity.
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 description does not add any new information beyond the parameter descriptions already in the schema. The example values are also present in the schema, so no additional meaning is provided.
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 verb 'creates' and the resource 'Workbench Transport Request in SAP'. It also distinguishes from sibling tools by indicating it is a prerequisite before write_abap_object, and specifies the return value (transport number).
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 explicitly says 'Do this before write_abap_object', providing clear guidance on when to use the tool. While it does not mention when not to use or alternatives, the context is sufficient for the agent.
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?
No annotations provided, so description carries full burden. It reveals the critical ordering constraint and that it writes to SAP via ADT REST, but lacks details on side effects, error behavior, or prerequisites beyond order.
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?
Single paragraph with front-loaded purpose and critical rules. Uses all-caps for emphasis, though could be slightly more structured. Effective and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema or annotations, the description provides the essential ordering but misses return value info, error handling, and does not relate to sibling tools (e.g., when to use write vs validate_and_activate).
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 80%, baseline 3. The description adds no extra detail per parameter beyond what the schema provides, though the ordering context indirectly relates to object_type. Marginal added value.
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?
Description states specific verb 'writes' and resource 'ABAP object to SAP via ADT REST'. The critical order differentiates it from siblings like analyze_module_pool or check_released_cds, making its purpose unmistakable.
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?
Explicitly provides a required sequence of object types with constraints like 'NEVER write BDEF before CDS views'. Also states 'One object at a time only', giving clear when-to-use and when-not-to-use guidance.
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?
No annotations provided, so description must cover behavior. It states checks and returns mapping, which implies read-only. Could add details about side effects or permissions, but for a check tool this is acceptable.
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?
Two sentences plus a key annotation about Clean Core. Front-loaded with step number and mandatory nature. Every sentence adds value, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given single parameter and no output schema, description fully explains purpose, input, output ('returns cds_source_mapping'), and workflow position. No gaps for AI agent.
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?
Only one parameter 'tables' with schema description already good (100% coverage). Description adds context that these come from analyze_module_pool, but no new syntax or format details beyond 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?
Description uses specific verb 'checks if SAP has released CDS views' and resource 'tables from Module Pool'. Mandatory step before generate_rap_skeleton distinguishes it from siblings like analyze_module_pool and generate_rap_skeleton.
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?
Explicitly labeled 'STEP 1b — MANDATORY before generate_rap_skeleton' and gives rationale about Clean Core. Does not explicitly state when not to use, but context implies after analyze_module_pool.
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?
With no annotations, the description carries the full burden. It clearly states it does NOT write to SAP and requires human approval, which are critical behavioral traits. It does not mention any side effects or destructive actions, which is appropriate for a code-generation step.
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?
Two sentences with no wasted words: the step number, action, what is generated, what is not done, and the approval gate are all present and front-loaded.
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?
Given the tool's complexity (generates multiple code artifacts) and no output schema, the description covers the essential components (CDS view, Behavior Definition, etc.) and the key constraint (no writes). It could be slightly more explicit about the return format, but is still fairly complete.
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% with good descriptions for each parameter. The description adds context by linking analysis_json to analyze_module_pool, but does not provide additional semantic depth beyond the schema defaults.
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 it generates a full RAP migration plan as ABAP code strings, identifying it as Step 2 and distinguishing it from siblings like analyze_module_pool (Step 1) and write_abap_object (actually writes to SAP).
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 explicitly says when to use it (Step 2 after analysis) and that human approval is needed before writing. It implies when not to use through step context but lacks explicit exclusion statements.
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 bears full burden. It discloses that the tool pauses for human input and shows specific summaries. Does not mention side effects, but the behavior is clear and non-destructive.
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?
Two sentences, no waste. Purpose and key usage details are front-loaded. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description fully covers the tool's role, when to use, required parameters, and what the human must do. No output schema is needed for this tool's simple interaction.
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 80%, and the description maps its summary fields to parameters (e.g., 'ANALYSIS SUMMARY' to my_analysis) but adds little new detail beyond the schema's own descriptions.
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?
Description clearly states the tool acts as a mandatory checkpoint showing the human what was done, analysis, and next action. It distinguishes from sibling tools by specifying it must be called before write_abap_object or validate_and_activate.
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?
Explicitly states the tool must be used between every step and always before write_abap_object or validate_and_activate. Also tells the human must type YES/MODIFY/ABORT to proceed.
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?
The description details the return value (structured JSON with screens, modules, etc.) but does not explicitly state whether the tool is read-only or has side effects. Since no annotations are provided, the description carries the burden; it is fairly transparent but could explicitly note non-destructive 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 sentences, front-loaded with the purpose. Each sentence serves a clear function: stating the action, providing usage guidance, and summarizing output. No unnecessary words.
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?
Given the tool's complexity (analyzing modules pool with rich output) and the lack of an output schema, the description adequately covers what is returned. However, it could benefit from mentioning the structure of the JSON output more explicitly, but it remains complete enough for agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% already, so baseline is 3. The description adds context by explaining that source_code must be combined from GetProgram and GetInclude calls, and gives an example for program_name. This adds meaning beyond the schema descriptions.
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: analyzing Module Pool source code. It explicitly mentions the resource (module pool source code) and the action (analyze). Sibling tools like check_released_cds or create_transport are unrelated, making this tool distinct.
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?
The description provides explicit prerequisites: first use GetProgram and GetInclude to fetch source, then pass the combined source here. This tells the agent exactly when to use this tool and what steps precede it, effectively differentiating from alternatives.
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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