workbench

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

The description is consistent with annotations (readOnlyHint, idempotentHint) and adds that the tool returns a table of per-record results. It discloses shared arguments and input format, but does not mention any potential limits or error behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the purpose, and each sentence adds necessary context without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately explains the return value (table of per-record results). It covers input, tool selection, and args, making the tool's behavior clear for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage, the description still adds value by explaining that input is multi-FASTA or one sequence per line, and that args are shared. This clarifies usage beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Run' and resource 'one SeqBench tool over many records', distinguishing it from sibling tools that operate on single records.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use this tool (batch processing) and how to specify input, tool, and args. It implicitly contrasts with using individual sibling tools for single records, but does not explicitly state when not to use.

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

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

Annotations declare readOnlyHint and idempotentHint true, so safety is covered. The description adds valuable behavioral details like auto-detection of molecule type and the list of reports. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, information-dense sentence that front-loads the purpose and quickly enumerates key outputs. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Without an output schema, the description adequately lists return components (composition, ORFs, enzymes, etc.) and a BLAST link. It covers core aspects but could mention formatting or limits.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear param descriptions. The description links parameters (maxOrfs, minOrfAa, endPrimerLength) to the reported features (ORFs, end primers), adding context beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool auto-detects molecule type and provides a comprehensive 'tell me everything' analysis. It distinguishes itself from sibling tools like find_orfs or gc_content by being an all-in-one summary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when a quick overview is needed, contrasting with specialized sibling tools. While not explicitly stating when not to use, the context provides sufficient guidance.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating a safe, repeatable simulation. The description aligns with this (returns product/primers) but adds no further behavioral traits beyond what annotations supply.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the action and output. It contains zero unnecessary words and conveys the core functionality efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complex tool with 11 parameters and no output schema, the description is adequate but lacks details on return format or expected outputs beyond 'product and junction primers.' However, the rich input schema compensates, making this sufficient for typical use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema fully documents all 11 parameters. The description adds no additional parameter details beyond naming the assembly methods, which is already implied by method enum values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: assembling fragments using three specified methods (Gibson/overlap, Golden Gate, restriction–ligation) and explicitly mentions the output (product and junction primers). This distinguishes it from sibling tools like virtual_gel or restriction_sites.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for cloning simulations but lacks explicit guidance on when to choose this tool over alternatives or when not to use it. No context about prerequisites or limitations is provided.

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

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

Annotations already declare readOnlyHint and idempotentHint, so safety profile is clear. The description adds specific behavioral context: outputs include per-codon adaptiveness, rare-codon flagging, and GC3 analysis. No contradictions, and it provides useful detail beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, no wasted words, front-loaded with the key output (CAI). Structure is clear and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers main outputs (CAI, per-codon adaptiveness, rare-codon, GC3) and mentions the host dependency via organism parameter. Missing details about return format or validation constraints, but for a 4-parameter tool without output schema, it is mostly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 3 of 4 parameters with descriptions (sequence, frameStart, rareThreshold), but organism parameter lacks description in schema. The tool description does not add any additional meaning to parameters; it only restates the overall purpose. Baseline 3 is appropriate since schema does most of the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies the tool calculates Codon Adaptation Index and per-codon relative adaptiveness, with rare-codon and GC3 analysis against an expression host. It clearly states the verb (analyse/calculate) and resource (CAI, adaptiveness), and the function is distinct from sibling tools like gc_content or codon_optimize.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies it is for CAI analysis of a CDS against a host, but does not explicitly state when to use it versus alternatives like codon_optimize or gc_content. No when-not-to-use or prerequisite guidance is provided.

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

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

Beyond annotations (readOnlyHint, idempotentHint), the description adds behavioral context by noting that coding DNA/RNA is accepted and translated in frame +1 first. This reveals the tool's input handling beyond static annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence of 20 words, front-loading the core purpose without any filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description omits what the tool returns (e.g., optimized sequence or string). The purpose is clear, but the lack of output specification is a gap for a tool that generates a result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 50% schema description coverage, the description adds meaning by linking the 'organism' parameter to the 'expression host' concept, though it does not explicitly explain the enum values. The protein parameter is well-described in the schema, so the description offers moderate additional value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb (codon-optimise), the resource (protein or coding DNA), and the method (picking most-frequent codon per residue). It distinguishes the tool from siblings like translate and reverse_translate by specifying the unique functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention when not to use it or reference sibling tools, leaving the agent to infer usage context.

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

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

Annotations indicate readOnlyHint and idempotentHint, which are consistent with 'lint' operation. Description does not add behavioral details beyond annotations, but also does not contradict them. For a read-only tool, the bar is lower, yet more context (e.g., that it returns a report of issues) would be helpful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence that is front-loaded with the verb 'lint' and immediately conveys the tool's purpose. No wasted words, though splitting into two sentences could improve readability slightly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While parameters are well-documented in schema and the tool's purpose is clear, the description does not mention return value format, error conditions, or limitations. For a tool with 7 parameters and no output schema, more context would be beneficial.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%; each parameter has a clear description. The tool description does not add parameter-level details, which is acceptable given full schema coverage. Baseline score of 3 appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description uses specific verb 'lint' and resource 'coding DNA sequence', and enumerates specific checks (premature stops, internal RBS/polyA motifs, unwanted restriction sites, GC extremes, repeats). This clearly distinguishes it from sibling tools like motif_finder or gc_content which focus on individual aspects.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description implies use for initial QC of a construct but does not explicitly state when to use this tool versus alternatives. No exclusions or prerequisites are mentioned.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds no significant behavioral detail beyond implying a read-only scoring operation. This meets the minimum bar but does not elaborate on edge cases or limitations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the core functionality. Every word is informative, and there is no redundancy or unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 4 parameters and no output schema. While the description conveys the primary action, it does not mention the format of the results (e.g., list of guides with scores, positions) or behavior for invalid inputs, making it only moderately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema coverage is 100% with detailed parameter descriptions. The tool description does not add any parameter-specific information beyond what the schema already provides, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: finding and scoring candidate guide RNAs for specific nucleases. It uses a specific verb-resource combination and lists the supported nucleases, distinguishing it from sibling tools like primer_design or motif_finder.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no explicit guidance on when to use this tool versus other alternatives. It does not mention when not to use it or provide context for selecting among sibling tools.

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

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

Annotations already indicate read-only and idempotent behavior; the description adds minimal extra context (screening for stable heterodimer) but doesn't detail error handling or output specifics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence that is short, front-loaded, and communicates the core purpose without fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given low complexity and no output schema, the description adequately explains the tool's purpose, though it could hint more at the output format or edge cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters; the tool description does not add additional meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'screen' and the resource 'two oligos' to find the most stable heterodimer, distinguishing it from siblings like 'oligo_analysis'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like 'oligo_analysis' or prerequisites; lacks contextual usage directions.

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

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

Annotations already mark the tool as readOnlyHint=true and idempotentHint=true, so the description only needs to add behavioral context beyond safety. It successfully discloses the types of calculations (molar mass, amount, concentration, copy number) and the input constraints (mass, volume, length/sequence), which is valuable transparency for a calculator tool with no side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, information-dense sentence that front-loads the core purpose and lists key inputs. No extraneous words: every phrase carries meaning (nucleic-acid, quantity conversions, specific units, input parameters). It is well-structured for quick parsing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters and no output schema, the description covers the main outputs and inputs. However, it omits important details: that the 'volumeUl' default of 0 means volume is unknown and concentration will not be computed, and that 'sequence' overrides 'length' (though this is noted in the schema for length, not in the description). These gaps reduce completeness for a tool that requires understanding optionality and dependencies.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so parameters are already documented. The tool's description adds value by explaining how parameters relate in the overall calculation (e.g., 'from mass ± volume and either a length or a sequence'), helping the agent understand the purpose without needing to infer from the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it performs nucleic-acid quantity conversions (molar mass, amounts, concentrations, copy number) from mass/volume and length/sequence. However, it does not explicitly differentiate from sibling tools that also deal with nucleic acids, such as gc_content or melting_temperature, though its focus on quantity conversion is fairly unique.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains what the tool does but provides no guidance on when to use it versus alternatives, nor does it mention any prerequisites or exclusions. For example, it does not clarify when to prefer this tool over other calculations like molarity from sequence composition tools.

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

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

Annotations already indicate read-only and idempotent. Description adds that it flags caveats, which reveals potential issues. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, no filler. All information is front-loaded and earn its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 2-param read-only tool with no output schema, the description is complete enough. It could be slightly more explicit about the return value (buffer recommendation), but is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage with descriptions for enzymeA and enzymeB, so the description adds no additional meaning. Baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool recommends a single NEB buffer for double digestion, with specific verb 'Recommend' and resource 'single NEB buffer'. It is distinct from any sibling tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when needing a buffer for two enzymes, but does not provide explicit when-to-use or when-not-to-use guidance, nor alternatives. Adequate but lacks exclusions.

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

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

The description adds meaningful behavioral context beyond annotations: it searches all six frames, implies start codon ATG, and the parameters document min length and require stop. Annotations already declare readOnlyHint=true and idempotentHint=true, so no need to repeat. However, it doesn't describe output format, which would be helpful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that is front-loaded and contains no wasted words. It efficiently conveys the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (ORF finding in six frames) and the lack of an output schema, the description is somewhat incomplete. It does not describe what the tool returns (e.g., coordinates, sequences, lengths), which an agent might need to use the output effectively. However, the parameters are well-documented.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with clear descriptions for each parameter. The description does not add extra meaning beyond the schema, so 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool finds open reading frames (ATG...stop) across all six frames. The verb 'find' and resource 'ORFs' are specific, and the mention of six frames distinguishes it from siblings like 'translate' or 'motif_finder'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. With many sibling tools (e.g., 'translate', 'motif_finder'), an agent would benefit from explicit usage context, such as when to use find_orfs instead of other sequence analysis tools.

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

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

Annotations already provide readOnlyHint=true and idempotentHint=true, indicating safe, repeatable behavior. The description lists transformations but does not explain order of operations, whether input is modified in place, or if any state changes occur. For a transformation tool without external side effects, the description adds moderate clarity beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads all key operations. Every word is essential; no fluff. It efficiently conveys the tool's capabilities without redundant details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters and high schema coverage, the description summarizes the tool's purpose adequately. It omits details like FASTA input acceptance (mentioned in schema) and default behavior order, but these are covered by the schema. For a formatting tool with no output schema, this is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is high (83%) with clear param descriptions. The description provides a high-level summary of operations that map to params (e.g., 'DNA↔RNA convert' maps to 'convert' param). It adds minimal new meaning beyond the schema, as the param descriptions already detail each option. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly lists the operations (clean, case-fold, convert, reverse, line-wrap) with specific verbs. It distinguishes from siblings like reverse_complement (which includes complement) by implication, though not explicitly. A slight gap is not explicitly contrasting with sibling tools that do individual operations (e.g., reverse_translate).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs. sibling tools like reverse_complement, translate, or sequence_format_convert. The description implies a general formatting purpose but does not state when this tool is preferred (e.g., for multi-step formatting) or when alternatives are better (e.g., for simple reverse complement or translation).

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating a safe analysis. The description adds value by specifying the exact outputs (GC content, AT content, per-base composition) beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with no wasted words, efficiently conveying the tool's purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple calculation tool with a single parameter and safety annotations, the description is mostly sufficient. However, it omits handling of invalid input or return format details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single parameter, with a clear description of acceptable input. The tool description does not add additional semantic detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states it computes 'GC content, AT content and per-base composition of a sequence', providing a specific verb+resource. It clearly distinguishes itself from sibling tools like 'characterize_sequence' which might have broader scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives. Siblings like 'characterize_sequence' or 'codon_adaptation_index' might overlap, but the description does not mention exclusions or preferred contexts.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds behavioral traits (IUPAC-aware, allows mismatches, handles circular templates) that are not fully captured by annotations, providing useful context beyond them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence of 15 words, front-loaded with the core purpose. No wasted words; every phrase adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of the tool (no output schema, 5 well-documented params), the description covers key capabilities. It could mention that this tool is for simulating PCR with known primer sequences (vs. designing primers), but that is implicit.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all parameters. The description repeats aspects (IUPAC-aware, mismatches, circular) that are already in parameter descriptions, adding minimal semantic value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool predicts PCR products for a template and pair of primers, with specific capabilities (IUPAC-aware, allows mismatches, handles circular templates). This distinguishes it from siblings like primer_design (which designs primers) and melting_temperature (which calculates Tm).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool vs alternatives. While the description implies it is for simulating PCR with given primers (as opposed to designing them), it does not provide explicit context or exclusions.

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

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

Annotations already indicate readOnlyHint and idempotentHint. The description adds context on the calculation methods (nearest-neighbour, Wallace, salt-adjusted) and outputs, which provides transparency beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that efficiently conveys all essential information. It is front-loaded and every part adds value, with no redundancy or wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having 5 parameters and no output schema, the description explains the methods and outputs sufficiently for a simple Tm calculator. It provides enough context for an agent to understand the tool's purpose and behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with all parameters described. The description does not add new information about parameters beyond the schema, so it meets the baseline but does not enhance understanding further.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool calculates melting temperature for primers/oligos, specifies methods (nearest-neighbour, Wallace, salt-adjusted), and mentions outputs (recommendation and molecular weights). This clearly differentiates it from siblings like primer_design or oligo_analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide explicit guidance on when to use this tool versus alternatives. It only describes what it does, without mentioning prerequisites, conditions, or alternative tools for specific scenarios.

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

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

Annotations already provide readOnlyHint and idempotentHint. The description adds valuable behavioral context beyond these: it specifies overlapping occurrences, searching both strands, and allowing mismatches. This is helpful for understanding tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, 13-word sentence that contains no extraneous information. Every word is necessary, and it front-loads the core functionality efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of an output schema, the description adequately covers the main purpose and behavioral constraints. However, it does not hint at the return format (e.g., positions or counts), which would be helpful for an agent. Slight gap prevents a perfect score.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description does not elaborate on parameters beyond the schema, providing no additional semantics or usage details for the four parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool finds overlapping occurrences of an IUPAC motif on either strand, allowing mismatches. This specific verb-resource combination (find occurrences of an IUPAC motif) distinguishes it from sibling tools like find_orfs or restriction_sites.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to use this tool versus alternatives. While it implies usage for IUPAC motif finding, it does not mention exclusions or compare with related tools among the numerous siblings.

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

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

Annotations already indicate read-only and idempotent. Description adds method ('Center-star') and output specifics, but does not disclose constraints like sequence length limits (schema mentions up to 25, but description omits). No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, no filler. Could be slightly more detailed without being verbose, but structure is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, and description barely explains what 'consensus' and 'per-column conservation' mean. For a complex MSA tool, more detail on output format would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and parameter description is clear. Tool description adds no additional input semantics beyond schema (only mentions output features). Baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states verb ('Center-star multiple sequence alignment'), resource ('multi-FASTA input'), and outputs ('consensus and per-column conservation'). Distinguishes from sibling 'pairwise_alignment'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies usage for multiple sequences but does not explicitly state when to use versus alternatives like 'pairwise_alignment'. No when-not-to-use or prerequisite guidance.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety profile is clear. The description adds behavioral value by mentioning 'warnings' and 'diagrams', indicating output includes safety checks and visual aids.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that efficiently conveys the tool's full scope. It is front-loaded with 'Full oligo analysis' and includes all key capabilities without extraneous words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description mentions diagrams and warnings, providing a reasonable expectation of output. Given the tool's complexity and strong annotations, this is nearly complete, though explicit return structure would be ideal.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema itself documents parameters adequately. The description does not add further parameter-level details (e.g., valid sequence formats), but this is not necessary given high coverage. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states 'full oligo analysis' and lists specific thermodynamic calculations (Tm/ΔG/ΔH/ΔS) and secondary structure screening (hairpin, self-dimer). This clearly distinguishes it from related siblings like melting_temperature and cross_dimer.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies comprehensive analysis but does not provide explicit when-to-use or when-not-to-use guidance relative to siblings. The agent must infer usage from the tool's scope, which is a minor gap.

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

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

Annotations already provide readOnlyHint and idempotentHint, so the description adds value by specifying the two alignment modes and scoring details, without contradicting annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded with key information (global/local, algorithms, scoring), no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the essential distinction and scoring, but could be improved by mentioning output type or alignment result, especially given no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is high (83%); the description mentions match/mismatch/gap scoring which is already in the schema. It does not add significant new meaning beyond what parameter descriptions provide.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs pairwise alignment of two sequences, specifies the algorithms (Needleman-Wunsch and Smith-Waterman), and mentions scoring components, distinguishing it from sibling multiple_sequence_alignment.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use (pairwise alignment) but does not explicitly state when to use this tool versus alternatives like multiple_sequence_alignment or provide exclusion criteria.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds that the tool parses into specific components, but does not disclose potential limitations, error handling, or performance characteristics. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that efficiently communicates the tool's purpose without any unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers input (GenBank flat file) and output structure (locus, definition, features, sequence). Given no output schema, this is sufficient, though explicit mention of the output format (e.g., JSON) would enhance completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage, with the 'text' parameter well-described. The tool description adds no additional parameter meaning beyond the schema's existing detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Parse' and the resource 'GenBank flat file', and specifies the output components (locus, definition, features, sequence). It effectively distinguishes this tool from siblings like format_sequence or parse_sanger_trace.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a GenBank flat file is available, but provides no explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among sibling tools.

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

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

Annotations already indicate read-only and idempotent behavior. The description adds value by detailing what the tool extracts (base calls, quality, traces, peaks), going beyond the annotations. It does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence. It uses a colon to list outputs, making it efficient and easy to parse. Every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of the tool (2 parameters, no output schema), the description covers the main purpose and outputs. However, it could be more explicit about the return format (e.g., JSON structure) since no output schema is provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters. The tool description adds no additional meaning to the parameters beyond what the schema provides, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool decodes Sanger ABIF chromatograms and lists specific outputs (base calls, quality, traces, peak locations), using a precise verb and resource. No sibling tool performs this function, so it is well-distinguished.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies use when the user has an ABIF file, but does not explicitly state when not to use it or suggest alternatives. Given the tool's unique niche, this is adequate but lacks explicit exclusions.

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

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

Annotations already indicate read-only and idempotent behavior. The description adds value by specifying it detects features on both strands and listing examples. However, it lacks details on detection methods, confidence scoring, or output format, which would be helpful for full transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the core action and includes relevant examples. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one input and no output schema, the description covers the types of features detected but does not explain the output format or whether it handles circular sequences. It is adequate but leaves some gaps for typical use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'sequence' is well-described in the schema (100% coverage). The description does not add extra semantics beyond the schema but mentions the types of features detected, which slightly enriches context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool auto-detects common cloning features on both strands, listing specific examples like promoters, tags, origins, etc. It distinctly differentiates from sibling tools such as find_orfs or motif_finder by focusing on cloning-related features.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 find_orfs or restriction_sites. There is no mention of prerequisites, limitations, or scenarios where this tool is preferred.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating no side effects. The description adds context about the penalty-picker algorithm and constraints used for scoring. This extra detail is valuable but not extensive, and there is no contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the main purpose and then lists the scoring constraints. It is concise with no redundant words, every part adds value. This is an ideal structure for a tool description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 19 parameters and no output schema, the description adequately explains what the tool does and which constraints are applied. However, lacking an output schema, it would be beneficial to mention the form of the output (e.g., ranked list of primer pairs with scores). The description is mostly complete for a read-only, idempotent tool, but missing output format details prevents a perfect score.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 47%, meaning the schema provides descriptions for 9 of 19 parameters. The tool description does not elaborate on individual parameters, instead summarizing the constraint categories (length, Tm, GC, 3'-clamp, structure). This adds some context but does not compensate for the undocumented parameters. With moderate coverage, a score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'De-novo PCR primer design (Primer3-style penalty picker)' with specific constraints (length, Tm, GC, 3'-clamp, structure). It uses a specific verb ('design') and resource ('PCR primers'), and distinguishes from siblings like 'in_silico_pcr' or 'oligo_analysis' by focusing on de-novo design.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives such as 'oligo_analysis' or 'cross_dimer'. The usage context is implied by the purpose (designing primers from scratch), but no exclusions or comparative guidance are provided. For a tool with many siblings, more explicit guidance would improve the score.

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

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds valuable context about what is reported (position, length, neutral mass). No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence; front-loaded with purpose. Could be slightly more structured but efficient overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 6 parameters fully described in schema and output fields mentioned, the description is fairly complete. Lacks usage notes but sufficient for a single-purpose tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 additional meaning beyond the schema. The baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('cleave') and resource ('protein'), and clearly states the output: each peptide's position, length, and neutral mass. This distinguishes it from sibling tools like motif_finder or restrict_sites.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for digestion but does not provide explicit guidance on when to use it versus alternatives, nor does it mention when not to use it. The context from name and siblings is weak.

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

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

Annotations already communicate readonly and idempotent behavior. The description adds algorithmic style (sliding-window, scale selection) but does not disclose error handling or output format. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-front-loaded sentence that conveys key information without redundancy. Every word serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and moderate complexity, the description could hint at the output format (e.g., array of scores). It adequately describes input but leaves the agent guessing about return structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description reinforces the purpose (sliding-window, scale) but adds no new parameter-level details beyond what the schema already provides (e.g., scale enum documentation, window clamping).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it computes a 'sliding-window hydropathy/hydrophobicity profile' using 'a published amino-acid scale', which is a specific verb-resource pair. The mention of 'ProtScale-style' and the sibling tool list (e.g., protein_properties, gc_content) makes it distinct from other sequence analysis tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the tool's function but does not explicitly state when to use it over alternatives or indicate exclusions. Usage is implied by the tool's specific focus on hydrophobicity, but no direct guidance is provided.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true. The description adds valuable behavioral context by enumerating the computed properties (molecular weight, GRAVY, etc.), which goes beyond annotations. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence that front-loads the main purpose ('Protein properties') and lists key outputs. No extraneous words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 2 parameters and no output schema, the description adequately covers what the tool does. It enumerates the computed properties, which is essential. Could mention return format, but not necessary for this simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with both parameters (sequence and chargeStep) well-described. The description lists the computed properties, which adds context, but does not add significant semantic detail beyond the schema for the parameters themselves.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool computes specific protein properties (molecular weight, isoelectric point, GRAVY, extinction coefficient, composition). It distinguishes itself from sibling tools like 'protein_hydrophobicity' which likely only computes hydrophobicity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives (e.g., protein_hydrophobicity, gc_content) or when not to use it. No prerequisites or context are given.

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

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

Description says 'Generate a random sequence', implying creation, but annotations have readOnlyHint=true, which is contradictory. Additionally, idempotentHint=true suggests repeated calls yield the same result, which for a random sequence is unlikely without seeding. The description does not address these discrepancies.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with no wasted words. Every element is necessary and front-loaded. Achieves high information density.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given three parameters and no output schema, the description should cover return format (e.g., output is a string) and address the contradiction between annotations and behavior. It omits these, leaving the agent uncertain about idempotency and read-only semantics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds value for the 'kind' parameter by explicitly listing DNA, RNA, and protein, which the schema's enum does not describe. It also mentions the optional GC content, aligning with the gcContent parameter. The schema already describes 'length' well, so this supplements the missing parameter description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the verb 'Generate' and the resource 'random DNA, RNA or protein sequence'. The optional GC content detail adds specificity. This distinguishes it from sibling tools like 'gc_content' (which computes GC of existing sequences) and 'reverse_complement'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for creating synthetic sequences with optional GC control. While no explicit when-not or alternatives are given, the tool's unique purpose among siblings makes its usage context clear.

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

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is clear. The description adds no further behavioral context (e.g., error handling, output format). It minimally extends annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, 9-word sentence that efficiently conveys the purpose without redundancy. It is properly front-loaded and contains no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, the description does not clarify what the returned data looks like (e.g., positions, cut sites). While the schema is well-described, the lack of output details limits completeness for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameters are already described in the schema. The description adds no additional meaning for either 'sequence' or 'enzymes', earning the baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool finds restriction enzyme recognition sites in a DNA sequence, using a specific verb and resource. It distinguishes from sibling tools like 'double_digest' or 'cloning_simulate' by focusing on site identification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 vs alternatives. Siblings include related tools like 'double_digest', but no context is given for selection or exclusion.

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

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

Annotations already declare readOnlyHint and idempotentHint, indicating a safe, deterministic operation. The description adds that it handles DNA/RNA sequences, which complements the annotations without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no superfluous words. It efficiently conveys the tool's core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Missing critical details: the description lists three operations (reverse, complement, reverse complement) but does not explain how the user chooses which operation to perform (no parameter for operation). No output description is provided despite no output schema, leaving return format unclear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description mentions DNA/RNA sequences, which relates to the 'type' parameter but does not explicitly explain how to specify the type. Schema covers 'sequence' description but not 'type', leaving some ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs reverse, complement, and reverse complement operations on DNA/RNA sequences. It distinguishes from siblings like translate or format_sequence by its specific nucleotide manipulation focus.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the name and description; users can infer when to use this tool for reverse complement operations. However, no explicit guidance on when not to use or alternatives is provided.

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

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

Annotations declare readOnlyHint and idempotentHint, indicating no side effects. The description adds algorithmic details (most-frequent codon per organism, degenerate IUPAC consensus) beyond annotations. It does not mention edge cases like stop codons or output format, but this is minor.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the core purpose ('Back-translate a protein to DNA') and concisely captures the key variant behavior. No extraneous words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple tool (3 parameters, no output schema), the description covers the essential behavior and mode differences. It lacks mention of output format or error cases, but these are likely obvious for such a tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explains the meaning of the two modes (frequent vs degenerate) and notes that organism is ignored in degenerate mode. With 67% schema coverage, it adds value beyond the schema, though it does not detail the 'protein' parameter beyond what is in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action (back-translate) and resource (protein to DNA), and distinguishes the two modes (frequent vs degenerate). It differentiates from siblings like 'translate' (DNA to protein) and 'codon_optimize' (optimizes existing DNA).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for converting protein to DNA but provides no explicit guidance on when to use this tool versus alternatives like 'translate' or 'codon_optimize'. No 'when not to use' information is included.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds value by detailing the output (identity, mismatches, insertions, deletions). No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, well-structured sentence that front-loads the action and is concise without superfluous words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main purpose and output. However, it does not mention that the read input can be provided either as FASTA text or as a base64 ABIF file, which is a minor gap given the schema allows both. Overall, it is mostly complete for a tool with good schema coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with clear descriptions for all parameters. The description does not add extra meaning beyond the schema, which is adequate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Align') and clearly identifies the resource ('Sanger ABIF read to a reference') and output ('report identity plus every mismatch, insertion and deletion'). This distinguishes it from siblings like parse_sanger_trace (which extracts trace data) and pairwise_alignment (general alignment).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for comparing Sanger reads to a reference but does not explicitly state when to use this tool over alternatives such as parse_sanger_trace or pairwise_alignment. No 'when not to use' guidance is provided.

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

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

Annotations already declare readOnlyHint and idempotentHint. The description adds context that raw sequence is treated as single-record FASTA and mentions the qualityOffset parameter for FASTQ. This goes beyond annotations by clarifying input handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that efficiently conveys the tool's purpose and key statistics with no unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lists the statistics but does not describe the output format (e.g., a JSON object with those metrics). Since there is no output schema, the agent may be unclear about the return structure. However, the list of stats provides reasonable inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, but the description adds nuance: 'raw sequence is treated as single-record FASTA' for the input parameter. The qualityOffset parameter remains well-defined by the enum and default. This adds slight value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states it provides statistics for FASTA or FASTQ files, listing specific metrics: count, length distribution, N50, GC content, and mean quality (for FASTQ). This clearly distinguishes it from sibling tools like 'gc_content' which only computes GC content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for comprehensive sequence statistics but does not explicitly state when to use this tool versus alternatives like 'gc_content' or 'sequence_report'. No exclusions or comparisons are given.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety and idempotency. The description does not add behavioral context beyond this, but does not contradict annotations either.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence without unnecessary words. Every phrase adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description provides a high-level overview but does not mention constraints like CDS extraction requiring GenBank input. The schema covers these details, so completeness is adequate but not rich.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the description reinforces enum values and format options. It does not add new parameter semantics beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the verb 'Convert' and the resources 'FASTA', 'GenBank', and 'TSV', with suboptions like CDS or protein. It distinguishes the tool's purpose from siblings like 'parse_genbank' or 'format_sequence', though not explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description lacks any guidance on when to use this tool versus alternatives like 'format_sequence' or 'parse_genbank'. No exclusions or context for selection are provided.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds that it produces a 'composite report' with a 'copyable text block,' which is consistent. No contradictions, but lacks rich behavioral context beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence front-loads key information: one-click, composite report, components. No waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (composite analysis with multiple outputs) and the presence of annotations and schema, the description adequately explains the report contents. No output schema exists, but the description compensates by listing components.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all parameters with descriptions (100% coverage). The description mentions the report components but doesn't add meaning beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'One-click DNA analysis: composition, ORFs, restriction-enzyme scan (single cutters) and end-primer Tm composed into a single report.' It uses a specific verb ('analysis') and resource ('DNA'), and distinguishes itself from sibling tools that focus on individual analyses.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this composite tool versus individual sibling tools (e.g., find_orfs, restriction_sites). The description implies convenience but doesn't specify trade-offs 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.

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safe, idempotent operation. The description adds no further behavioral traits such as what the output contains or any limitations. It is adequate but provides no extra value beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that immediately conveys the tool's purpose and key features. Every word earns its place, with no fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 14 parameters and no output schema, the description is too brief. It fails to explain what the tool returns (likely primer sequences), how parameters interact (e.g., editKind conditions), or provide any workflow context. The tool is complex, yet the description offers minimal completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description mentions 'nucleotide substitution or an amino-acid codon swap' which aligns with editKind, but does not add meaning beyond the schema's parameter descriptions. No extra context for parameters like armTmTarget or oligoNM.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool designs site-directed mutagenesis primers, specifying two styles (QuikChange overlapping or Q5 back-to-back) and two edit types (nucleotide substitution or amino-acid codon swap). This is specific and distinguishes it from sibling tools like primer_design.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, nor when to choose between the two primer styles. It lacks context on prerequisites or suitable scenarios, relying solely on the parameter schema.

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

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

The description adds context about translation and standard code, but does not clarify that only forward frames are available (contradicting 'all six frames'). Annotations already indicate read-only and idempotent behavior. No disclosure of input handling or stop codon behavior beyond schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Very concise single sentence, front-loads the core purpose. However, the inaccuracy about frames undermines efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Lacks positioning among siblings, no mention of output format, and unclear about reverse complement functionality. Given the absence of an output schema, the description should clarify output type and behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 67% schema coverage, baseline is 3, but the description adds no parameter-specific details and misleads about frames. It does not explain the 'toStop' parameter's effect beyond what schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool translates nucleotide sequences to protein and mentions frames and standard code. However, it says 'all six frames' while the input schema only allows frames 1,2,3 (single frames), creating ambiguity about whether reverse complement frames are supported.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives like reverse_translate or codon_optimize. No mention of prerequisites or context for frame selection.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds value by specifying output format (HGVS g. notation) and optional coding effects, which goes beyond annotations. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, appropriately sized sentence that front-loads the main purpose with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately hints at output via 'HGVS g. notation' and optional amino-acid effects. Parameters are fully covered. Some details like handling of no variants are omitted, but overall it is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear parameter descriptions. The description adds that coding effects are optional and relates frameStart to coding, but this adds only marginal meaning beyond the schema, matching the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool aligns a query to a reference and calls variants in HGVS g. notation, with optional coding effects. This specific verb-resource combination distinguishes it from sibling tools like pairwise_alignment or sanger_vs_reference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for variant calling but does not explicitly state when to use this tool versus alternatives like pairwise_alignment or sanger_vs_reference. No exclusion criteria or context are provided.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description's 'predict' aligns with safe, read-only behavior. The description adds minor context about gel migration but does not substantially enhance transparency beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence of 13 words, front-loading the main purpose with no unnecessary words. Extremely concise and structured well.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple simulation tool with full schema coverage and no output schema, the description adequately explains the core functionality. It could mention output format (e.g., image or table), but the purpose is clear enough for agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with all parameters described. The description mentions 'chosen DNA ladder' corresponding to the ladder parameter, but adds no new information beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool predicts restriction-digest fragment sizes and gel migration positions against a DNA ladder. The verb 'predict' and resource are specific, but it does not explicitly distinguish from sibling tools like 'double_digest' or 'restriction_sites', though the gel visualization aspect is unique.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives (e.g., 'restriction_sites' for just sites, 'double_digest' for double digests). It lacks 'when to use' or 'when not to use' instructions.

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

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

The annotations declare readOnlyHint=true and idempotentHint=true, while the description says 'Run a multi-tool pipeline' implying execution of tools that may modify data. This is a contradiction. Beyond annotations, no behavioral traits (e.g., side effects, error handling) 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core purpose, every part is necessary. No redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity and zero output schema, the description lacks details on return values, error handling, execution order guarantees, and valid tool names. It covers the basics but leaves gaps for a user to fully understand behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 50% schema description coverage, the description adds meaning to both parameters: input format (multi-FASTA or one per line) and steps structure (ordered list with tool, args, from). This supplements the schema well.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool runs a multi-tool pipeline over many records, specifying the structure of steps and input format. It effectively distinguishes from sibling tools which are individual sequence analysis operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the chained sequence of steps and the role of 'from' for overriding source, but does not explicitly state when not to use this tool or mention alternatives. The context is clear enough for an AI agent to understand its main use case.

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