Server Quality Checklist

Tool Scores

• generate_barcodeC
  2.9/5.0
  Behavior2/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  With no annotations, the description carries the full burden of disclosure, but it only states the output format (PNG image) and supported symbologies. It does not explain the return value representation, error handling, size limits, or any side effects. This is insufficient for an agent to anticipate tool behavior reliably.

  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 a single, front-loaded sentence that conveys the core functionality and supported formats without redundancy. Every word earns its place, and it is appropriately sized for a relatively simple tool.

  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?

  The tool has 6 parameters, no output schema, and no annotations, yet the description provides minimal context. It doesn't explain the actual return format (e.g., file path, base64 data), how errors are surfaced, or the difference between 1D barcodes and QR handling. This is incomplete for an agent to use the tool correctly without additional assumptions.

  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 description coverage is 100%, so each parameter is already documented with meaningful descriptions. The tool description adds no additional parameter semantics beyond what the schema provides, such as cross-parameter dependencies (e.g., height ignored for QR). The baseline of 3 is appropriate given full schema coverage.

  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 clearly states the tool generates barcodes and QR codes as PNG images, listing specific symbologies. However, the overlap with sibling tool 'generate_qr' is not addressed, so the description doesn't fully distinguish when to use this tool rather than that one. The verb and resource are specific, but sibling differentiation is incomplete.

  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 is provided on when to use this tool versus alternatives like 'generate_qr' for QR codes or 'bulk_barcode' for multiple barcodes. The description doesn't mention any conditions, exclusions, or preferred scenarios. The agent is left to infer usage solely from the tool name and sibling list.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• generate_qrA
  4/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  With no annotations, the description carries the full burden of behavioral disclosure. It discloses the output format (PNG) and its wrapper relationship to generate_barcode, but does not mention side effects, error behavior, or limitations. For a simple generation tool, this is acceptable but not rich.

  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 only two sentences, with the core action in the first sentence and the sibling relationship in the second. No filler or redundant information.

  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 simple 3-parameter schema and full schema coverage, the description provides enough context to understand the tool's purpose and output. The lack of output schema means return format is implied by 'PNG image', which is adequate but not explicit.

  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?

  The input schema covers 100% of parameters with descriptions, so the baseline is 3. The description does not add further meaning to parameters like data, scale, or eclevel beyond what the schema already states.

  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 generates a QR code as a PNG image, using a specific verb and resource. It distinguishes itself from generate_barcode by explicitly calling itself a convenience wrapper for QR, so an agent knows this is the QR-specific option.

  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 mentions it is a convenience wrapper around generate_barcode for QR, implying that for QR code generation this tool is preferred over the more general generate_barcode. However, it does not explicitly state when to use alternatives like bulk_barcode or decode_barcode, so guidance is helpful but not fully explicit.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• decode_barcodeA
  4.1/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  With no annotations provided, the description does the job of disclosing core behavior: it takes an image (base64 or path) and returns decoded values and formats. It doesn't mention potential limitations or edge-case behavior, but for a read-only decode operation, it provides adequate 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?

  Two sentences, front-loaded with purpose and formats. Every sentence is informative with no filler or redundancy.

  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?

  The description explains the return value and input options, but the schema allows zero required parameters, and the description doesn't explicitly state that at least one of path/base64 must be provided. This ambiguity could lead an agent to call with no input, so it isn't fully 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?

  The schema already covers all three parameters with descriptions (100% coverage). The description adds no extra meaning beyond stating the input can be base64 or file path, which is already in the schema. It doesn't clarify the mutual exclusivity of path/base64 or that none are formally required.

  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 uses the specific verb 'Decode' and clearly identifies the resource as barcodes from an image, listing many format examples. It is distinct from the sibling tools which are generation/encoding tools.

  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 tool's purpose as a decoder is clear and contrasts with siblings that generate/encode barcodes. However, it doesn't explicitly state when to choose this over alternatives or mention any exclusions, but the context is sufficient for most use cases.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• bulk_barcodeA
  4.2/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  With no annotations, the description carries the full burden of behavioral disclosure. It discloses the output format (one PNG per item) and the hard limit of 50, which are key runtime behaviors. While it does not mention side effects or permissions, this is a non-destructive generation task, so the transparency is adequate and exceeds the minimum.

  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 two sentences, each serving a distinct purpose: stating the bulk action and specifying the output behavior with a cap. It is front-loaded and free of unnecessary detail, making it highly efficient.

  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 moderate complexity (5 parameters, no output schema, no annotations), the description provides the core purpose, output format, and an important constraint (cap). It does not explicitly describe parameter interactions or defaults, but the schema covers these, making the description sufficient for most use cases.

  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 description coverage is 100%, meaning every parameter is already documented in the schema. The description adds no parameter-specific details beyond the list input, so it does not need to compensate for gaps. A baseline score of 3 is appropriate because the schema carries the explanatory weight.

  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 generates many barcodes/QR codes at once from a list, which is a specific verb+resource combination. It distinguishes itself from siblings like generate_barcode and generate_qr by emphasizing bulk operation, and the output detail (one PNG per item, capped at 50) adds further clarity.

  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 implies the intended use case—batch generation from a list—and the cap at 50 suggests handling multiple items. However, it does not explicitly name alternatives or state when not to use this tool (e.g., for a single barcode). The sibling names provide context, but the description itself lacks explicit exclusions.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• encode_epcA
  4.2/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states the tool computes a value and does not physically program a tag, and it lists the outputs (EPC hex, tag URI, binary). It does not cover potential validation errors or edge cases, but for a pure computation tool, the key behavioral traits are disclosed.

  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 two sentences long and front-loaded with the action and target. It efficiently states the inputs, outputs, and a crucial caveat without redundancy or fluff. Every sentence adds value.

  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?

  Although there is no output schema, the description explicitly states the return values (EPC hex, tag URI, and 96-bit binary), which is essential for a tool with no structured response definition. It also clarifies the scope (computes, not physically writes). It does not provide examples or detailed scheme-specific guidance, but given the schema richness, it is sufficiently complete for an agent to use correctly.

  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?

  The input schema already provides 100% coverage for all five parameters, each with detailed descriptions. The tool description adds minimal extra meaning beyond naming the inputs in prose. Since the schema does the heavy lifting, a baseline score of 3 is appropriate.

  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 begins with a specific verb 'Encode' and clearly identifies the resource (SGTIN-96, SSCC-96, or GIAI-96 EPC for UHF RFID tags). It lists the exact input types and distinguishes itself from sibling tools that deal with barcodes/QR codes rather than RFID EPC encoding.

  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 implies when to use this tool: for computing EPC values for UHF RFID tags. It explicitly states what it does not do ('does not program a physical tag'), providing a clear exclusion. However, it does not name alternative tools or compare itself to siblings, though siblings are clearly different in purpose.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.