schematic-pdf-mcp
Server Quality Checklist
Latest release: v0.2.0
- Disambiguation5/5
Each tool targets a distinct stage of the PDF conversion pipeline: inspection, conversion, and validation. There is no overlap in their purposes, making selection unambiguous.
Naming Consistency5/5All tool names follow a consistent verb_noun snake_case pattern (inspect_schematic_pdf, convert_schematic_pdf, validate_schematic_ir). This is highly predictable and readable.
Tool Count5/5With 3 tools, the set is well-scoped for a specialized schematic PDF conversion workflow. Each tool serves a necessary function without redundancy or bloat.
Completeness5/5The tool surface covers the full lifecycle from inspecting a PDF to converting it to JSON and validating the resulting IR. No critical missing operations are apparent for the stated domain.
Average 3.2/5 across 3 of 3 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
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool saves raw, semantic, and final JSON artifacts, which implies file-writing side effects. However, it does not state whether it overwrites files, what error handling occurs, or whether it is idempotent, leaving important behavioral details unclear.
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 concise sentence that states the action and outcome without extraneous words. It is front-loaded and efficient, though it uses jargon ('four-layer baseline') that could be expanded. Overall, it is appropriately sized.
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?
The tool has two parameters, no output schema, and no annotations, yet the description gives only a high-level summary. It does not explain the meaning of 'four-layer baseline', what the JSON artifacts look like, or how the pages parameter affects conversion. For a tool with siblings, this lacks sufficient context for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides zero information about the input parameters. With 0% schema description coverage and no mention of source_path or pages in the description, the agent has no understanding of what parameters mean or how to populate them. The description completely fails to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs a conversion and saves specific JSON artifacts. The verb 'Run' combined with 'conversion' and the tool name 'convert' make the purpose clear. It distinguishes from siblings ('inspect' and 'validate') by indicating a conversion/output-producing step, though it does not explicitly compare to 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?
There is no explicit guidance on when to use this tool versus the sibling tools. The mention of 'baseline conversion' implies a standard conversion process, but no prerequisites, exclusions, or alternative references are provided. Usage is only implied by the tool's name and general function.
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?
With no annotations, the description must disclose behavioral traits. It states the action (inspect and classify) but does not explicitly confirm it is read-only, mention permissions, or describe error behavior or side effects. The term 'inspect' implies non-destructive, but this is not explicit.
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, front-loaded sentence with no redundant information. Every word contributes to understanding the tool's purpose, achieving high conciseness and clarity.
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?
The tool is simple (one parameter, no output schema), but the description lacks context about return values, classification criteria, or how the results might be used. Agents are left without information about what the tool outputs, making it incomplete for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has a single parameter `source_path` with no description (0% schema coverage). The description adds minimal value by implying that `source_path` refers to the local PDF file, but it does not elaborate on path format, required extension, or any restrictions.
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 function: inspect a local PDF and classify each page as vector, raster, hybrid, or empty. It uses specific verbs (inspect, classify) and specifies the resource (local PDF) and output categories, making it distinct from sibling tools like convert or validate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool instead of alternatives. The description does not mention prerequisites, intended scenarios, or compare with sibling tools such as convert_schematic_pdf or validate_schematic_ir.
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?
The description discloses a key behavioral guarantee (non-mutating), but lacks details on validation semantics, error reporting, or output/exit behavior. With no annotations available, this leaves significant uncertainty.
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 single sentence is concise, front-loaded, and contains no filler. It states the action, resource, and a key constraint efficiently.
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?
For a one-parameter validation tool, the description gives the core action and parameter type, but omits details like what validation entails, how results are returned, and any error handling. Given no annotations or output schema, this is a moderate gap.
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 description clarifies that 'ir_path' refers to a local JSON file path, which the schema does not convey beyond the title 'Ir Path'. However, it does not specify path constraints (relative/absolute, extension, etc.).
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 a specific action (validate) on a specific resource (local SchematicIR JSON file) and adds a constraint (without changing semantic content), which distinguishes it from sibling PDF tools.
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 usage when you have a local SchematicIR JSON file to validate, but it does not explicitly compare to sibling tools or state when not to use it. No alternative tools are mentioned.
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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- Evaluate tool definition quality.
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