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Multiplex PCR panel design

multiplex_panel_design
Read-onlyIdempotent

Choose one primer pair per target so the whole panel works in one tube: no cross-dimer between any two of the primers, every amplicon resolvable from every other on the gel you will run, and one annealing temperature that serves all of them. Searches combinations rather than picking each target's best pair in isolation, which is what makes panels fail — and when no compatible panel exists it names the target pairs that cannot be multiplexed at all, so you know which one to redesign.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetsYes2-8 targets to amplify in one reaction.
ampliconMaxNoPanel-wide default product size ceiling.
ampliconMinNoPanel-wide default product size floor, for targets that set none.
maxTmSpreadNoWidest Tm difference tolerated across every primer in the panel, in °C — one annealing temperature has to serve all of them.
agarosePercentNoGel the panel will be read on. Omit and the percentage whose resolving window contains the amplicons is chosen and reported — a panel of small products judged on a 1% gel reads as all-comigrating, which is about the gel rather than the primers.
dimerThresholdDGNoΔG (kcal/mol) at or below which a cross-dimer involving a primer's 3' END is a conflict. That end is where extension starts, so it matters at a weaker ΔG than an internal pairing.
candidatesPerTargetNoCandidate pairs considered per target (max 6). More finds a panel where fewer cannot, at the cost of a larger search.
internalDimerThresholdDGNoThe looser bar for a cross-dimer that pairs internally and only sequesters primer.

TDQS

A4.1/5.0
Behavior4/5

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

The description explains key behaviors: it searches combinations rather than isolated pairs, and on failure it identifies the problematic target. No side effects are mentioned, but annotations indicate read-only and idempotent, so the description aligns with expected behavior without overpromising.

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

Conciseness4/5

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

The description is concise and well-structured in two sentences, packing essential information about constraints, search strategy, and failure behavior without unnecessary detail. It avoids redundancy with the schema.

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

Completeness4/5

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

Given the schema and annotations, the description provides sufficient context about why multiplexing is challenging, what the tool does about it, and what happens when no panel exists. It doesn't discuss output format, but since there's no output schema, the description's coverage is adequate.

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

Parameters3/5

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

The schema already provides 100% coverage and detailed descriptions for all parameters (including defaults like 'dimerThresholdDG' and 'candidatesPerTarget'). The description doesn't add parameter-specific information beyond what's in the schema, so it doesn't improve on the baseline.

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

Purpose5/5

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

The description clearly states the tool's function: selecting one primer pair per target for a multiplex panel with constraints like no cross-dimer, amplicon resolution, and uniform annealing temperature. It distinguishes from single primer design by highlighting the combinatorial search, making its purpose unambiguous.

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

Usage Guidelines4/5

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

The description implicitly contrasts with single-primer tools (e.g., 'primer_design') by emphasizing the panel-level search and the failure mode that names the target that cannot be multiplexed. While it doesn't explicitly say 'use this when you need multiplex', the context makes it clear when this tool is appropriate versus alternatives.

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

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TDQS

A3.6/5.0
Disambiguation4/5

Most tools have highly specific purposes (e.g., crispr_grna_design vs base_editing_design vs prime_editing_design). However, there is some overlap in sequence analysis tools (characterize_sequence, sequence_report) and plasmid annotation tools (plasmid_annotate vs plasmid_deep_annotate) which could cause confusion.

Naming Consistency3/5

The naming pattern is largely consistent with snake_case verb_noun or noun_descriptor (e.g., primer_design, plasmid_annotate, fastq_trim). However, there are exceptions like 'batch', 'workflow', 'gc_content', and 'cloning_diagnose' which don't follow the verb_noun pattern consistently. Also, some names are phrases like 'golden_gate_from_parts'.

Tool Count2/5

With 101 tools, this server is extremely large and likely overwhelming for agents. Even for a comprehensive bioinformatics toolkit, this exceeds a manageable scope, risking agent confusion and inefficient tool selection. A more modular approach would be advisable.

Completeness4/5

The tool surface covers a wide range of bioinformatics workflows including sequence analysis, primer design, cloning, CRISPR, NGS, expression analysis, and data export. There are minor gaps such as lack of a dedicated protein structure prediction tool and limited off-target genome coverage, but overall the set is impressively complete for its domain.

Resources